994.40%. ”.5“: L 8. 7L» £-\-.. 3.. 2,1 5.3! I :25. c . A a .\I .. I. , ..y.l|..1t r...r- 2......»1. J2 faulty}. (g. :. .ln ... n (93'095362, J MICHIGAN STATE UNIVERSITY Ll Mill Hill! HIIlilllmlllllll “ 3 1293 00599 5398 LIERARY Michigan State University This is to certify that the thesis entitled A Systems Model Analysis of the Transmigrant Family Productivity and Returns presented by Kartiko Hari Respati has been accepted towards fulfillment of the requirements for Masters degree in Agric. Engr. Tech. flat/p .k. K Major professor Date August 1, 1988 0-7639 MS U is an Affirmative Action/Equal Opportunity Institution PLACE IN RETURN BOX to tomovo this checkout from your record. TO AVOID FINES return on or baton duo duo. DATE DUE DATE DUE DATE DUE g—fifil l MSU Is An Affirmative Action/Equal Opportunity Institution A SYSTEMS MODEL ANALYSIS OF THE TRANSMIGRANT FAMILY PRODUCTIVITY AND RETURNS BY KARTIKO HARI RESPATI A THESIS . Submitted to Michigan State University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE in Agricultural Engineering Technology Department of Agricultural Engineering 1988 i If! r‘ ABSTRACT m A SYSTEMS MODEL ANALYSIS OF THE TRANSMIGRANT FAMILY PRODUCTIVITY AND RETURNS By Kartiko Hari Respati The capability of a transmigrant family in cultivating their land with different assumed labor, animal , and tractor inputs was studied in this research. A system approach was used for the analysis methodology. A computer model was formulated to simulate different labor and resource inputs to evaluate the working capability of a transmigrant family. The general objective of this study was to develop a framework for the analysis and evaluation of the optimum area of land that a transmigrant family could effectively cultivate under various conditions and with different inputs. The specific objectives are 1. Establish a database from available secondary sources of information on manhours required for the cultivation of various crops under various new land conditions. 2. Consider family labor and resources available. 3. Develop a systems model for evaluation of the critical parameters pertaining to optimum land utilization capability of transmigrant families. 4. Evaluate the cost and return data for land preparation with a hand tractor, a bullock, and manual labor. Conclusions of this study are as follows : A systems model was developed and tested for the productivity of a transmigrant family which provides the means to study productivity and land utilization under a variety of conditions and with different input resources. The simulation studies made provide examples of how the systems model might be utilized in the planning of land and resource allocation for transmigrant families. Based on assumptions made, a transmigrant family of four with no outside laborers could utilize 1.9 ha of land with a orOp mix of paddy, beans, and cassava; or a crop mix of corn, beans, and cassava. Based on assumptions made, a transmigrant family’s farm income was Rp 218,914 for a custom-hired bullock, Rp 230,951 for a custom-hired tractor, and Rp 306,831 for a transmigrant family owned a tractor. ACKNOWLEDGEMENTS The author whishes to express his sincere gratitude to the following : Dr. Merle L. Esmay, the author’s major professor and committee chairman, for his guidance during the graduate program, and for his encouragement during this work and his editorial help while writing the manuscript. Dr. Thomas H. Burkhardt and Dr. Robert 0. Barr, who served on the author’s guidance committee, for their helpful suggestions and their editorial help while writing the manuscript. The Ministry of Transmigration of The Republic of Indonesia for the financial support. Dr. Suprodjo and Mr. Sumangat of Gadjah Mada University of Yogyakarta for their help and support for data collection of this work. ii TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES Chapter 1. INTRODUCTION 1.1. THE COUNTRY 1.2. TRANSMIGRATION 1.2.1. History of Transmigration 1.2.2. Transmigration Program 2. OBJECTIVES 3. REVIEW OF LITERATURE 3.1. 3.2. AGRICULTURAL HAND-TOOLS LAND CLEARING OPERATION FOR FOREST LAND . Underbrushing . Cutting and Felling . Stockpiling . Windrowing and Burning . Harrowing and Spreading Rock Phophate D CLEARING OPERATION FOR ALANG-ALANG SS (IMPERATA CYLINDRICA) Rub a >~z howmonaw m C)? oawwooaw .1. First Plowing 3.3.2. First Harrowing 3.3.3. Second Plowing and Harrowing CLIMATE 3.4.1. Agroclimatic Zones iii vi ix «10:0: 10 10 3.4.2. Distribution of Rainfall CROP WATER REQUIREMENT 3.5.1. Crop Coefficient (Kc) 3.5.2. CrOp Evapotranspiration (ET crop) WATER BALANCE POWER INPUTS REQUIREMENT CROP MANAGEMENT COLLECTION CHARACTERISTIC OF AREA STUDY CROP WATER REQUIREMENT WATER BALANCE POWER INPUTS AVAILABILITY 4.4.1. Human Resource 4.4.2. Animal-Drawn Power 4.4.3. Tractor Power CROPPING ROTATION AND THE TRANSMIGRANT RETURNS MODEL DEVELOPMENT AND SIMULATION FOR TRANSMIGRATION FAMILY MODEL 5.1. 5.2. 5.3. SYSTEM APPROACH FOR TRANSMIGRATION FAMILY MODEL Background Information Problem Definition Systems Identification Systems Linkage mount» thH HHHH TRNASMIGRATION FAMILY MODEL 5.2.1. Farmsize Analysis 5.2.2. Productivity Analysis SYSTEMS SIMULATION INPUTS iv 18 21 21 23 25 28 30 30 31 38 4O 40 42 43 45 45 45 45 46 49 so 51 56 62 6. SYSTEM SIMULATION OUTPUTS AND DISCUSSION 6.1. CULTIVABLE AREA ANALYSIS 6.2. LABOR SURPLUS ANALYSIS 6.3. PRODUCTIVITY AND RETURNS ANALYSIS 6.4. ANALYSIS OF POWER INPUTS USED IN LAND PREPARATION 7. CONCLUSIONS AND RECOMMENDATIONS 7.1. CONCLUSIONS 7.2. RECOMMENDATIONS FOR FUTHER RESEARCH LIST OF REFERENCES APPENDIX A APPENDIX B APPENDIX C APPENDIX D 66 66 67 7O 77 81 81 83 84 87 9O 93 110 TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE 1.2. 3.2. 3.4. LIST OF TABLES Indonesia Population by Provinces and Islands Based on Data from Central Bureau of Statistic Percentage of Area and Population Density in Indonesia by Provinces and Islands Various Operation, Power Inputs, and Equipment Used for Rice Cultivation for One Hectare of Land Various Operation, Power Inputs, and Equipment Used for Corn Cultivation for One Hectare of Land Various Operation, Power Inputs, and Equipment Used for Beans Cultivation for One Hectare of Land Various operation, Power Inputs, and Equipment Used for Cassava Cultivation for One Hectare of Land Production Inputs Required for Different Crops for One Hectare of Land Projected Production for Different Crops Based on One Hectare of Land Various Field Operation for Different Crops During One Year Period Average Monthly Rainfall in Tajau Pecah During 1952 - 1976, Probability of The Rainfall at 75 X, and Monthly Rainfall in 1977 Values of Crop Coefficient (Kc) for Paddy Rice Planted in Different Months Values of Crop Coefficient (Kc) for Corn Planted in Different Months Values of Crop Coefficient (Kc) for Beans Planted in Different Months vi 25 26 27 27 28 28 29 32 34 35 35 TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE 4.9. Crop Evapotranspiration (ET crop) per Month for Paddy Rice Planted in Different Months (mm) Crop Evapotranspiration (ET crop) per Month for Corn Planted in Different Months (mm) Crop Evapotranspiration (ET crop) per Month for Beans Planted in Different Months (mm), Surplus of Water per Year for Paddy Rice Planted in Different Months in Transmigration Project of Tajau Pecah Surplus of Water per Year for Corn and Beans Cultivation Planted in Different Months in Transmigration Project of Tajau Pecah Distribution of Manhours Requirement per Hectare for Traditional Crops Present Cropping Rotation and Planted Area for Different Crops in Transmigra- tion Project of Tajau Pecah Financial Analysis of a Transmigration Family Production The Composition of a Unit labor Timetable for Planting, Growing, and Harvesting Traditional Crops Simulated Labor Input Units for Land Preparation (man) Simulated Size of Cultivable Area with Different Assumed Labor Inputs for Land Preparation Simulated Labor Availability Condition for Each Simulation for Different Assumed Labor Inputs (manhours) The labor Surplus by Months based on Labor Requirement of Each Simulation (manhours) vii 36 37 38 39 39 42 43 44 52 57 64 66 68 69 TABLE TABLE TABLE TABLE TABLE TABLE TABLE 6.9. 6.10. Simulated Production of Each Traditional Crop for Different Assumed Labor (Kg) Simulated Productivity of a Unit Labor to Produce Traditional Crops for Each Simulation (Kg / Unit Labor) Simulated Financial Analysis of Transmigrant Family for Each Simulation (Rupiah) Timetable for Planting, Growing, and Harvesting Selected Crops for Simula- tion 5 (without Corn) Timetable for Planting, Growing, and Harvesting Selected Crops for Simulation Six (without Paddy Rice) Result from the two simulations Simulated Results of Assumed Power Inputs viii 70 71 72 74 74 75 78 FIGURE FIGURE FIGURE FIGURE FIGURE FIGURE FIGURE 4.1. 5.1. LIST OF FIGURES Map of the Republic of Indonesia System of Agroclimatic Classification for Rice—Based Cropping Pattern October Rainfall During a Period of 63 years for Tanggerang, Indonesia, Arranged in Chronological Order (a) and in Ranking Order (b) Distribution of Rainfall in Tajau Pecah Causal Loop for The Transmigrant Family Model Blackbox Diagram for Transmigrant Family Model Transmigration Family Model Flowchart ix 17 20 33 47 48 59 I. INTRODUCTION 1.1. The country Indonesia is the world’s largest archipelago. The Republic of Indonesia is composed of 13,667 islands. More than half of the islands are still unnamed and only seven percent are inhabitated. The archipelago stretches along the Equator between 94°45’ and 141°05’ East longitude and from 6008’ North to 11°15’ South latitude. The land area of Indonesia is about 1.9 million km2 and the sea area is about 9.9 million km'. Administratively, Indonesia is divided into 27 provinces with Jakarta as the Capital city (CBS, 1985). Based on the 1980 Population Census, the projected total population of Indonesia in 1985 was 165 million people. This makes it the fifth most populous country in the world after China, India, USSR, and USA. Sixty-one percent of Indonesia population (100 million) live on the island of Java (table 1.1.) which comprises only 6.9 percent of the total area of Indonesia. The population of density on Java was tabulated at 759 people per km' in 1985 (table 1.2.), thus giving evidence to an uneven distribution among islands as well as among provinces. Nearly two thirds of Java's farm families have less than one-half hectare of agricultural land. This is a subsistence size plot and it generates a low income for the farmers. This unevenly distributed population and the fact that most consists small-farm-households obstruct the development in both the inner islands (Java, Bali, and Lombok mHmmzoozH mo ujmnamm MI... mo am: 3 Table 1.1. The Population of Indonesia by Province_and Island Based on Data from The Central Bureau of Statistics. (Thousands of People) Province / island 1980 19855 Population x Aceh 2,611 3,604 1.82 North Sumatera 8,361 9,518 5.76 West Sumatera 3,407 3,695 2.24 Riau 2,169 2,534 1.54 Jambi 1,446 1,741 1.05 South Sumatera 4,630 5,543 3.30 Bengkulu 768 943 0.57 Lampung 4,625 6,033 3.65 Sumaterac 28,016 32,992 19.93 Jakarta 6,503 7,890 4.78 West Java 27,454 30,973 18.75 Central Java 25,373 27,145 16.44 Yogyakarta 2,574 2,290 1.81 East Java 29,189 31,281 18.94 Javac 97,270 100,279 60.72 Bali 2,470 2,659 1.61 West Nusatenggara 2,725 3,071 1.86 East Nusatenggara 2,737 3,053 1.85 East Timor 555 629 0.38 Nusatenggarac 8,457 9,411 5.70 West Kalimantan 2,489 2,837 1,72 Central Kalimantan 954 1,149 0.70 South Kalimantan 2,065 2,306 1.40 East Kalimantan 1,218 1,550 0.93 Kalimantanc 6,723 7,842 4.75 North Sulawesi 2,115 2,394 1.45 Central Sulawesi 1,289 1,551 0.94 South Sulawesi 6,062 6,651 4.03 Southeast Sulawesi 942 1,092 0.66 Sulawesic 10,410 11,688 7.08 Maluku 1,411 1,646 0.99 Irian Jaya 1,174 1,368 0.83 Indonesia 147,490 165,155 100.00 a: CBS,1985 b: projected island 4 Table 1.2. Percentage of Area and Population Density in Indonesia by Province / Island. (19855) Province / island Area Area Population Density km2 x X people/Km3 Aceh 55,392 2.88 1.82 54 North Sumatera 70,787 3.69 5.76 134 West Sumatera 49,778 2.59 2.24 74 Riau 94,562 4.93 1.54 27 Jambi 44,924 2.34 1.05 39 South Sumatera 103,688 5.4 3.3 53 Bengkulu 21,168 1.1 0.57 45 Lampung 33,307 1.74 3.65 181 Sumaterac 473,606 24.67 19.93 70 Jakarta 590 0.03 4.78 1,337 West Java 46,300 0.41 18.75 669 Central Java 34,206 1.78 16.44 794 Yogyakarta 3,169 0.17 1.81 943 East Java 47,922 2.5 18.94 653 Javac 132,187 6.89 60.72 759 Bali 5,561 0.29 1.61 478 West Nusatenggara 20,177 1.05 1.86 152 East Nusatenggara 47,876 2.49 1.85 64 East Timor 14,874 0.78 0.38 42 Nusatenggarac 88,488 4.61 5.70 106 West Kalimantan 146,760 7.65 1.72 19 Central Kalimantan 152,600 7.95 0.70 8 South Kalimantan 37,660 1.96 1.40 61 East Kalimantan 202,440 10.55 0.93 8 Kalimantanc 539,460 28.11 4.75 15 North Sulawesi 19,023 0.99 1.45 126 Central sulawesi 69,726 3.63 0.94 22 South Sulawesi 72,781 3.79 4.03 91 Southeast Sulawesi 27,686 1.44 0.66 39 Sulawesic 189,216 9.85 7.08 62 Maluku 74,505 3.88 0.99 22 Irian Jaya 421,981 21.99 0.83 3 Indonesia 919,443 100.00 100.00 180 a: CBS, 1985 b: Projected 0: Island 5 of West Nusatenggara province) and the outer islands (islands other than Java, Bali, and Lombok), therefore making transmigration; i.e., the resettlement of people in less densely populated areas, an important program' for the Indonesian government in its quest for a more equitable distribution of land. 1.2. Transmigration Transmigration is one of the major programs of the Indonesian government along with family planning and increasing food production. The term "Transmigration" is defined by the Government of Indonesia as : ... the removal and transfer of population from one area to settle in another area determined within the territory of the Republic of Indonesia, in the interest of the country’s development, or for other reasons considered necessary by the government. (Statute no. 3 of 1973 : The Basic Stipulations for Transmigration). From the definition above, transmigration is a national effort to carry out regional development; especially for the development of the provinces outside of Java, Bali, and Lombok (an island of West Nusatenggara province). It is also a process of allocating and reallocating human resources for regional development. 6 1.2.1. History of Transmigration The transmigration program was started in 1905 during the period of Dutch colonization. The original idea behind the transmigration program was a concern of the colonial government on the possibility of overpopulation in Java island (Swasono 1985). Raffles (1814) and Du Bus de Gisignies (1827) saw overpopulation as jeopardizing future colonization in Java. The limited land available along with overpopulation in Java drove the colonial government to implement the transmigration program. The purpose of the transmigration program at that time was to create the farming system for a rice-growing pattern utilizing irrigation and to send workers to government estates. The first group of transmigrants in 1905 consisted of 115 families from the province of Central Java who were sent out to Lampung province. From 1905 up to 1941 there were 257,313 people or 144,000 families who had been moved to the outer islands (Swasono 1985). The transmigration program was stopped from 1941 until 1949 when the second world war and the Indonesian independence war took place. The transmigration program was resumed in 1950 under the Indonesian government. By 1968, 101,240 families or about 424,000 people had been moved to the outer islands. In 1969 the government started its first five year national development plan. Since then, transmigration programs have been improved and by the third five year 7 national plan in 1985 457,572 families had been moved. 1.2.2. Transmigration program Transmigration has been coupled with another government program of increasing ‘food production through the implementation of extensive rice production. The transmigration program has opened new areas for paddy rice cultivation outside Java, Bali and Lombok. The program has also provided the opportunity of increasing food production through the use of high yield varieties, fertilizer, and application of appropriate mechanization. Resettlement under the official transmigration program has been based almost entirely on small-holder agriculture. There are six different farming systems in the Transmigration programs (Martono 1985): a. Farming systems with rainfed scheme b. Farming systems with irrigation scheme c. Farming systems for tidal areas d. Farming system with cash crops scheme e. Farming systems for fishermen and fish-breeding in coastal ponds f. Farming system based on animal husbandary Transmigrants are recruited in rural areas of Java, Bali, and Lombok. They must be married, of good character, and have previous farming experience. On arrival in the new area the transmigrants receive a small house on 0.25 ha of 8 village land, 1 ha of cleared farmland for foodcrop cultivation, and 0.75-1 ha of additional land for future development. The 0.25 ha of village land consists of a small house and garden for planting of vegetables, soybeans, groundnuts, and paddy. The one hectare of farmland is located next to the house and is for planting paddy, while 0.75-1 ha of additional land is situated outside of the village. Public facilities including schools and clinics are located in the village center. The transmigrants are also provided with selected agricultural equipment and supplies such as hoes, chopping knives, and seeds. Plans are that during the first year in the new area, the transmigrants should be able to cultivate their 0.25 ha of village land and the 1.00 ha of farmland. They are supplied with fertilizer and the basic needs (subsistence supplies) for survival. The land is supposed to be in a "cultivable condition". However, the transmigrants have to do additional land clearing from woods and covercrops before they can cultivate their land. II. OBJECTIVES Sumangat and Purwadi (1978) found that most of the transmigrant families can work only 0.7 hectare and thus leave the rest of their allocated land uncultivated. This results in an inefficient use of land and resources. An analysis is needed to establish the optimum amount of land under various conditions for the transmigrants and whether the transmigrants should be supplied with additional inputs (animal or tractor) for more effective utilization of the land and the welfare of the transmigrants. The general objective of this study is to develop a framework for the analysis and evaluation of the optimum amount of land that a transmigrant family can effectively cultivate under various conditions and with different inputs. The specific objectives are : 1. Formulate a database from available secondary sources on manhours required for the cultivation of various crops under specific new-land conditions. 2. Consider family labor and resources available. 3. Develop a systems model for evaluation of the critical parameters pertaining to the optimum land utilization capability of transmigrant families. 4. Evaluate the cost and return data for land preparation with a hand tractor, a bullock, and manual operation. III. REVIEW OF LITERATURE 3.1. Agricultural hand-tools Indonesian agriculture, which mainly consists of small farms, is carried out with human and animal power. The predominant source of power is human. Commonly used hand tools for farming in many areas of Indonesia are as follows (A.C. Pandya.1978) : a. Cangkul / pacul (hoe), b. Parang (chopping knife), 0. Sabit (sickle), d. Ani-ani (rice harvesting knife), e. Garpu tarik (forked hoe), f. Garpu alang-alang (forked hoe used for eradicating pernicious weeds called alang—alang or Imperata cylindrica), g. Linggis (crowbar), h. Kampak (axe), i. Sekop (shovel), j. Tajak (weeding hook), k. Ganco (mattock), 1. Slundak (tool for making water channels in the field), m. Tugal (sowing stick). Plowing and harrowing are done by 'Pacul’ (hoe), seeds are broadcast or sown by hand or 'Tugal’ (sowing stick), and 10 ll weed control is by 'Garpu alang-alang’ (forked hoe), or 'Tajak’ (weeding hoe). Rice harvesting is carried out by 'Ani—ani’ (harvesting knife) or by 'sabit’ (sickle). 'Parang’ (chopping knife) is used for chopping bush and grass, and 'Kampak’ (axe) for cutting tree stubs and branches. 'Sekop’ (shovel) is used for removing soil. The government give transmigrants some of these hand tools which consist of the following : a. 'Cangkul’ / 'pacul’ (hoe), b. 'Parang’ (chopping knife), 0. 'Tajak’ (weeding hook), d. 'Slundak’ (tool for making water channel in the field), e. ‘Ganco’ (mattok), f. 'Garpu alang-alang' (forked hoe), g. 'Linggis’ (crowbar). 3.2. Land Clearing Operation for Forest Land The objective of land clearing is to prepare the land for cultivation just prior to the rainy season. Clearing should be performed in a way which minimizes the disturbance of top soil. Mailangkay (1978) stated that land clearing chronological activities consist of 1. Underbrushing, 2. Cutting and felling, 12 3. Stockpiling the usable timber, 4. Windrowing and burning the jungle debris, 5. Harrowing on the contour and spreading rock phosphate on the harrowed area. 3.2.1. Underbrushing Underbrushing is a process of cutting brush, vines, and small trees. This activity is done either by manual operation using "parangs" or chopping knives and axes; or by a small crawler tractor of 100 bhp. During underbrushing, inspection and evaluation of the standing timber is carried out to determine the forest class for each area. An estimate of the number of trees is made by taking three random samples for each different kind of vegetation. The estimates are made by randomly locating two points 100 meters apart. The vegetative growth is measured and counted along a straight line between these points for a width of five meters on either side. This provides the population measure for 1/10 hectare. Caterpillar Co. classified the forest class based on diameter as follows (Caterpillar Performance Handbook): less than 30 cm 31 cm - 60 cm 61 cm - 90 cm 91 cm 120 cm 121 cm 180 cm 13 3.2.2. Cutting and Felling Cutting and felling is a process of selecting and cutting trees of 30 cm or greater diameter which are suitable for sawing into timber or for commercial uses. Trees with diameters larger than 30 cm are cut at breast height and the stumps are left, and trees smaller than 30 cm in diameter are sheared at ground level. The trees will be cut by chain saw or by other approved means. Thetimber will be stripped of branches and assembled into stockpiles at one kilometer distance apart. 3.2.3. Stockpiling The usable wood stockpiles are placed near to the main roads for transportation and sawing into lumber. The non- usable timber is placed in windrows and burned. 3.2.4. Windrowing and Burning After removal of the usable timber, the land clearing operation is continued with the clearing of all trees, brush, vines, stumps, and other debris. Special tools and equipment are used and the debris is placed in windrows 30 meters apart along the contour. Clearing and windrowing is done with crawler tractors equipped with multipurpose toOth—jungle rakes which allow soil to pass through. The windrows are burned after sufficient drying to ensure a hot, continuous burn of at 14 least 80 percent of the material. 3.2.5. Harrowing and Spreading rock phosphate After all debris has been burned, the final clearing of the areas is achieved by disc harrowing using heavy-duty harrows to a depth of approximately 30 or 40 cms, to cut out roots, subsurface stumps, and vegetation. All harrowing is carried out on the contour and is done in such a manner that the top soil is not burried and the subsoil is not to be exposed. After harrowing , the rock phosphate is spread on the harrowed areas at the rate of 500 kilograms per hectare. The rock phosphate should be crushed so that ninety percent will pass a 100 mesh sieve, and have a maximum moisture content of 1.5 X . 3.3. Land Clearing Operation for Alang-alang grass (Imperata cylindrica) Some of the transmigration sites have been developed from reclamation of large areas of alang-alang grass (Imperata cylindrica). Tajau Pecah, for instance, had alang- alang grass growing before it was chosen as a transmigration site. Sorjani (1970 in Soewardjo 1986) stated that in Indonesia it is estimated there are about 16 million hectares of alang-alang grass, and it is estimated that the area is 15 increasing by 150,000 to 200,000 hectares yearly. Shifting cultivation, especially in Sumatera and Kalimantan, plays a major role for increasing its population. Land clearing for alang-alang grass has been fully mechanized using crawler tractors and wheel tractors. Equipment used in land clearing Operations were disk plow and disk harrow. Land clearing operations consist of a first plowing, first harrowing, and a second plowing and harrowing. 3.3.1. First plowing First plowing is carried out to cut out and destroy the roots of the alang-alang. Roots of alang-alang are left in the sun for four weeks. 3.3.2. First harrowing First harrowing is done to expose and destroy the rest of the alang-alang rhizomes that were mixed with soil. 3.3.3. Second plowing and harrowing Second plowing and harrowing are the last operations and are intended to put the land into a condition that is free from alang-alang and ready for cultivating. 16 3.4. Climate Two topics are discussed in this sub-chapter, i.e. agroclimatic zones and distribution of rainfall. 3.4.1. Agroclimatic zones Oldeman (1980) classified the various rainfall distribution into five main agroclimatic zones for rice-based cropping pattern. He defined wet months as having 200 mm of monthly precipitation or more and dry months as having 100 mm of monthly precipitation or less. The main agroclimatic zones are as follows : Zone A : More than 9 consecutive wet months; Zone B : 7-9 consecutive wet months; Zone C : 5-6 consecutive wet months; Zone D : 3-4 consecutive wet months; Zone E : less than 3 consecutive wet months. The agroclimatic zones are sub-divided according to the length of the dry period, i.e. the number of consecutive dry months. If a dry period is less than two months, year-round cultivation of food crops is possible, and the growing period is 11 to 12 months. A dry period of 2 to 3 month requires careful planning for year-round cultivation. If the dry period lasts four to six months a fallow period is unavoidable, but two selective crops in sequence are possible. A dry period of 7 to 9 months, or a growing period of 3 to 5 months, allows the cultivation of only one food 17 \ crop. If the dry period is more than nine months, the area is not suitable for food crop production without an additional source of water. This classification system, which is applied in Indonesia, leads to a total of 18 agroclimatic zones (Figure 3.1.). 0 I2 I II 65 2 IO . . 3 9 . . Lenqtn oi growing penoo Length oi on period in months in months 4 8 5 E4 04 C4 7 8 6 (100 < P < 200) . (P < IOOnun/inonth) T 5 8 £3 03 C3 83 4 9 3 IO 2 £2 02 C2 02 A2 II I :2 EI on c: on AI 0 o’u’z'3'47575’7’efi9'm'u’u2 Length oI eet period ">200 nun/month) in months Figure 3.1. System of Agroclimatic Classification for Rice-based Cropping Pattern (FAO 1982) 18 The following is an illustration of the agroclimatic classification. Rainfall data of Tajau Pecah shows that there are six consecutive wet months and two dry months. The wet months of Tajau pecah are in C section of the agroclimatic system and can be found along the bottom line of the triangle. The dry months are located on the right line of the triangle. The cross section between the wet months and dry months is on C-2 section. Therefore, Tajau Pecah is classified in the C-2 zone using this system. 3.4.2. Distribution of rainfall Mean monthly rainfall data indicate only a trend of certain climate patterns. They can be useful in the indentification of agroclimatic zones, but do not provide any information on the rainfall variability (Oldeman, 1982). Yevjevich (1972) and Doorenbos & Pruitt (1977) used a probability method to calculate the distribution of rainfall. This method assumed that rainfall is normally distributed. To compute rainfall probability, rainfall records are arranged in decreasing order. Each record is assigned a ranking number (m). The highest rainfall of a particular year is then ranked as number one. The second highest rainfall of a certain year is ranked as number two and so on. The ranking numbers are then given probability levels Fa(m), which are calculated as follows : 19 Fa(m) = 100 t m / (n + 1) (3.1.) where : Fa(m) = probability level in percent m = ranking number n = number of recorded years To illustrate this method, an example from Oldeman (1982) will be shown. A 63-year monthly rainfall chart for October in Tanggerang, Indonesia, was arranged in decreasing order and each record was given a ranking number (m). To calculate the rainfall probability for rank number 20 (Figure 3.2.) is Fa (m) = 100 8 m / (n+1) Fa (20) = 100 x 20 / (63+1) = 31.25 %. This means that ranking number 20 has a rainfall probability of 31.25 % .The probability of at least 150 mm of rainfall during October is 31.25 % . To know which rank number has a probability level of 80%, a calculation can easily find this by substituting 80 % for Fa(m). Fa(m) = 100 t m / (n+1) 80% = 100 t m / 64 m = 51 This means that the 80% probability of rainfall is 40 mm or in 8 out of 10 years rainfall for October in Tanggerang is 20 Figure 3.2. October rainfall during a period of 63 years for Tanggerang, Indonesia, arranged in chronological order (a) and in ranking order (b). 21 at least 40 mm. This can be found by drawing a line from m = 51 to 40 mm at the bottom of the graph in figure 3.2. 3.5. Crop Water Requirement Crop water requirements are defined as the depth of water needed to meet the evapotranspiration water loss (ETcrop) under the following conditions (Doorenbos & Pruitt, 1977): 1. The planted crop is assumed free of disease, 2. Crop is growing in large fields, 3. Crop is planted under non-restricting soil, water and fertility conditions, 4. Crop is assumed to be achieving full production potential under the given growing environment. To calculate the crop water requirement, two topics are discussed : crop coefficient (Kc) and crop evapotranspiration (ETcrop). 3.5.1. Crop coefficient (Kc) Crop coefficient (Kc) is a ratio between crop evapotranspiration (ET crop) and the reference crop evapotranspiration (ETo) when the crop is grown in a large field under optimum growing conditions. The value of the crop coefficient (Kc) varies with the development stage of the crops. Coefficient values for 22 different crops can be found in Doorenbos & Pruitt (1984)-and Doorenbos & Kassam (1979). The values of Kc for the traditional crop used in this thesis can be found in the next chapter. 3.5.2. Crop evapotranspiration Crop evapotranspiration can be calculated with the following formula ET crop = Kc * ETo (3.2.) where : ET crop = crop evapotranspiration in mm / day or mm / month Kc crop coefficient ETo the rate of evapotranspiration from an extensive surface of 8 to 15 cm tall, green grass cover of uniform height, actively growing, completely shading the ground and not short of water (Doorenbos & Pruitt 1984), mm / day or mm / month. There are four methods to calculate ETo : 1. Blaney-Criddle method, 2. Radiation method, 3. Penman method, 4. Pan Evaporation method. 23 A complete calculation of these methods can be found in Doorenbos and Pruitt (1984, pp.3-34). Pan evaporation method was used in GMU research (1978). 3.6. Water balance In the calculation of the water balance, three assumptions were made (UGM,1979) 1. Depth of root zone Depth of root zone was assumed for paddy rice, corn, and beans as 40 cm. 2. Coefficient of run-off (Kr) The value of Kr was assumed to be 0.2. This value can be applied for areas which have relative humidity more than 70% and high rainfall distribution (Doorenbos & Pruitt 1975, in GMU 1979). Kr = 0.2 means that rainfall infiltration into the ground is 80% from total rainfall (Pt) in millimeters. 3. Water readily available for crops (Sa) Moisture content for clay soil for every 30 cm of depth of root was assumed as 4.5-6.0 cm of water (FAO, 1971 in UGM 1979). For further evaluation, moisture content for crops was assumed to be 5 cm of water for every 30 cm of depth of root. (GMU 1979). 24 Availability of water is calculated as follows : Sa = D t 5 cm/30 cm (3.3.) where Sa = availability of water, cm of soil water content D = depth of root in cm Surplus of water is calculated as follows (Pt - ET crop) SR = + Sa (3.4.) 10 where SR = surplus of water, cm of soil water content Pt = total rainfall, millimeter ET crop = crop evapotranspiration, milimeter Sa = availability of water, cm of soil water content 10 = conversion factor from milimeter to centimeter If SR is negative the ET crop > (Pt + Sa), and the crop is short of water. If SR is positive the ET crop < (Pt + Sa), and the crop has more than enough water available. If SR is equal to zero, ET crop = (Pt + Sa). 25 3.7. Power input requirements For determining labor requirements or other power inputs, a description of field operations, applied equipment, and the capacity of work for paddy rice, corn, beans, and cassava cultivation are presented on the following tables. The labor requirement values in the following tables will be used in analysis of labor surplus of the transmigration farmland model in chapter IV. Table 3.1. Various Operations, Power Inputs, and Equipment used for rice cultivation for One Hectare of Land (Hours). No. Field Operation Inputs Equipment Capacity (hours/ha) 1. First plowing animal moldboard 50 - 60 plow hand - rotary tiller 20 - 30 tractor 2. Second plowing animal moldboard 50 - 60 plow hand - rotary tiller 20 - 30 tractor 3. Harrowing animal comb harrow 20 - 40 hand - rotary tiller 10 - 20 tractor 4. Basic Manuring man 60 - 80 5. Planting man 150 - 170 6. Top dressing man 60 - 80 7. Weeding (3 X) man hoe, weeding 350 - 360 hook ' 8. Applying herbi- man sprayer 70 - 80 cides 9. Harvesting man sickle 370 - 380 Source : GMU 1978 26 Table 3.2. Various field Operations, Power Inputs, and Equipment Used for Corn Cultivation for One Hectare of Land (hours) Field Operations Inputs Equipment Capacity (hours/ha) 1. First Plowing animal moldboard 50 - 60 plow hand - rotary tiller 20 - 30 tractor 2. Second Plowing animal moldboard 50 - 60 plow hand - rotary tiller 20 - 30 tractor 3. Harrowing animal comb harrow 20 - 40 hand - rotary tiller 10 - 20 tractor 4. Manuring man 40 - 50 5. Planting man hoe 25 - 36 6. Weeding man hoe, sickle 200 - 280 7. Harvesting man sickle 18 - 24 Source : GMU 1978 27 Table 3.3. Various Field Operations, Power Inputs, and Equipment Used for Beans Cultivation for One Hectare of Land (Hours). No. Field Operations Inputs Equipment Capacity (hours/ha) 1. First Plowing animal moldboard 50 - 60 plow hand - rotary tiller 20 - 30 tractor 2. Second Plowing animal moldboard 50 - 60 plow hand - rotary tiller 20 - 30 tractor 3. Harrowing animal comb harrow 20 - 40 hand - rotary tiller 10 - 20 tractor 4. Manuring man 40 - 44 5. Planting man hoe 25 - 36 6. Weeding man hoe, sickle 200 - 280 7. Applying man sprayer 70 - 75 Herbicide 8. Harvesting man sickle 64 - 79 Source : GMU 1978 Table 3.4. Various Field Operations, Power Inputs, and Equipment used for Cassava Cultivation for One Hectare of Land (Hours)1. No. Field Operations Inputs Equipment Capacity (hours/ha) 1. Planting man 22 - 30 2. Harvesting man _ chopping 55 - 60 knives Source : GMU 1978 1 Cassava is planted simultaneously with corn or beans; therefore, the field operations of its cultivation are planting and harvesting. 28 3.8. Crops management Production inputs and projected production for different crops for one hectare of land can be seen on tables 3.5. and 3.6. Table 3.7. shows the monthly activities for each crop during a year. Table 3.5. Production Inputs Required for Different Crops for One Hectare of Land (Kilogram) No. Crops Seeds Fertilizer 1. Paddy rice 40 100 NPK + 50 TSP 2. Corn 30 30 NPK 3. Beans 50 50 NPK + 100 TSP Source : GMU 1978 Table 3.6. Projected Production for Different Crops Based on One Hectare of Land No. Crops Projected production (100 kg) 1. Paddy rice 15 2. Corn 8 3. Beans 7 4. Cassava 100 Source : GMU 1978 29 Crops During a One Year Period Table 3.7. Various Field Operations for Different Months Paddy rice Corn Beans Cassava January Weeding II Land prep. February Weeding III Basic mng. Land prep. March Harvesting Planting Basic mng. Plant. April Weeding Planting May Weeding June Harvesting Spraying July Harvesting August September Land prep. October Basic manuring November Planting Harvt. December Top Dressing & Weeding I Source GMU 1978 Rainfall data and analysis of crop water requirements will be used for determining the planting time of traditional crops on the simulation of the transmigrant family model. Based on the methods discussed above in regard to rainfall, water requirements and labor requirements, the data on the following chapter is collected. IV. DATA COLLECTION Secondary data for this study have been obtained mainly from research carried out at Gadjah Mada University (GMU) from 1977 to 1982 in Tajau Pecah, South Kalimantan. Other data sources has been the Central Bureau of Statistics (CBS) and the Ministry of Transmigration (MOT). 4.1. Characteristics of the Area Studied The GMU research was location specific at the transmigration project of Tajau Pecah village in South Kalimantan. The village is located in the district of Jorong, and the county of Tanah Laut. The distance between the village and Pleihari, the capital of Tanah Laut county, is 12 km. The distance between the village and Banjarmasin, the capital of South Kalimantan province, is about 77 km. Total area provided for the transmigration project in Tajau Pecah was 15,000 ha, out of which 2,000 ha had been used. Each family received 2.0 ha of land consisting of 0.25 ha for houselot and 1.75 ha for foodcrop cultivation. The transmigrants also received agricultural equipment consisting of : chopping knives, hoes, and crowbars. Most of the transmigrants provided themselves with other needed agricultural tools. The original vegetation of Tajau Pecah was Alang-alang grass (Imperata cylindrica). Most of the topography of Tajau Pecah was flat with a 4—6% of slope and some hills. Soil type 30 31 in Tajau Pecah was clay and was classified as red-yellow podzolik with 5-15 cm of top soil. The Tajau Pecah area is drained by the Swarangan River and several small tributaries, such as : Gunung Mangerang, Batu Bananjang, Munggu Rumbi, Langset Besar and Kuranji Bahalang. Water in these tributaries includes soil run-off resulting from local rains. 4.2. Crop Water Requirement Based upon classification of agroclimatic zones by Oldeman (1982), Tajau Pecah is classified in the C-2 zone which is characterized by a 5-6 month wet period and a 2-3 month dry period (Figure 4.1.) The distribution of rainfall for Tajau Pecah was taken during the year 1952-1976 (25 years) from the weather station at PT Gunung Mukti, 10-15 Km from Tajau Pecah. Monthly rainfall probability used in the analysis was assumed 75% and the possibility of failure of harvest was one out of every four years. The average values of monthly rainfall distribution and its probability are presented in table 4.1. Appendix A shows the data of monthly rainfall during 1952- 1976 for the transmigration project of Tajau Pecah. Rainfall data will be used for determining the planting time of each traditional crop used in the transmigrant family model. 32 Table 4.1. Average Monthly Rainfall in Tajau Pecah During 1952 - 1976, Rainfall which Has Probability 75%, and Monthly Rainfall in 1977 Months Average monthly P = 75% Rainfall rainfall1 1977 (mm) (mm) (M) January 378 272 290 February 279 206 346 March 308 185 372 April 218 141 354 May 169 84 121 June 138 48 138 July 131 47 1 August 74 28 25 September 95 14 0 October 139 55 67 November 275 199 125 December 397 256 396 1. 1952 - 1976 Source : Weather station of PT Gunung Mukti, in GMU Report on the Transmigration Projects in Tajau Pecah, 1978. ralntoll (mm) 33 MONTHS Figure 4.1. Distribution of Rainfall in Tajau Pecah, 1952 - 1976 Tables 4.2 to 4.4. present crop coefficient (Kc) for paddy rice, corn, and beans. The values of Kc were taken from Doorenbos and Pruitt (1977). 34 Kc will be used for determining crop evapotranspiration (ET crop) of traditional crop used in the simulations of transmigrant family model. Table 4.2. Values of Crop Coefficient (Kc) for paddy rice planted in different months Paddy rice planted in Months ----------------------------------------- September October November January - .95 1.05 February — - .95 March - - - April - - - May - — - June - - - July - - - August - - - September .88 - - October 1.10 .88 - November 1.05 1.10 .88 December .95 1.05 1.10 Source : Doorenbos & Pruitt (1977) Growing period : 30 / 30 / 30 - 35 / 20 - 25 RH :> 70% The values of the crop coefficient (Kc) varies with the development stage (growing period) of the crops. From the above table 4.2., development stages of paddy crops which is planted on September are 30 days for initial period with Kc = 0.88, 30 days for crop development period with Kc = 1.10, 30 - 35 days mid-season with Kc = 1.05, and 20 - 25 days late season with Kc = 0.95. Values of the crop coefficient is taken for area with relative humidity at least 70 % . 35 Table 4.3. Values of Crop Coefficient (Kc) for corn planted in different months Corn planted in Months ----------------------------------------- September October March April January - 0.55 - - February - - - - March - - 0.75 - April - ~ 0.80 0.75 May - - 1.05 0.80 June - - 0.55 1.05 July - - - 0.55 August - - - - September 0.75 - - - October 0.80 0.75 - - November 1.05 0.80 - - December 0.55 1.05 - - Source : Doorenbos & Pruitt (1977) Growing period : 20 / 30 / 30 / 20 or 20 / 30 / 40 / 30 RH : > 70% Table 4.4. Values of Crop Coefficient (Kc) for Beans planted in different months Beans planted in Months ----------------------------------------- September October March April January - 0.55 - — February - - - - March - - 0.75 - April - - 0.80 0.75 May - - 1.00 0.80 June - - 0.55 1.00 July - - - 0.55 August - — - - September 0.75 - - - October 0.80 0.75 - - November 1.00 0.80 - - December 0.55 1.00 - - Source : Doorenbos & Pluitt (1977) Growing period : 20 / 20 / 40 / 20 - 25 Rh : > 70% 36 Tables 4.5. to 4.7. show the values of water consumption requirement for paddy rice, corn, and beans. The values were taken from GMU research done in 1978. Table 4.5. Crop Evapotranspiration (ET crop) per Month for Paddy Rice Planted in Different Months (mm of soil water content) Crop Evapotranspiration Months ---------------------------------------- September October November January - 94 104 February - - 102 March - - - April - - - May - - - June - - - July - - - August - - - September 124 - - October 157 121 - November 110 106 92 December 109 120 126 Total annual ET 500 441 424 Source : GMU 1978 37 Table 4.6. Crop Evapotranspiration (ET crop) per Month for Corn Planted in Different Month (mm of soil water content) Crop Evapotranspiration (ET crop) Months ----------------------------------------- Sept October March April January - 55 - - February ~ - - — March - - 100 - April - - 110 104 May - - 124 94 June - - 59 113 July - - - 63 August - - - - September 78 ~ - - October 114 78 - - November 110 84 - - December 63 120 - - Total Annual ET 365 337 393 374 Source : GMU 1978 38 Table 4.7. Crop Evapotranspiration (ET crop) per Month for Beans Planted in Different Months (mm of soil water content) Crop Evapotranspiration (ET crop) Months ----------------------------------------- Sept October March April January - 54 - - February - - - - March - - 93 - April - - 111 97 May - - 114 94 June - - 59 108 July - - - 63 August - - - - September 78 - - - October 114 78 - - November 105 84 - - December 63 114 - - Total Annual ET - 360 330 377 362 Source : GMU 1978 4.3. Water Balance Calculation for water balance was based on distribution of rainfall and probability of occurence (75%). The surplus water values are presented in table 4.8. for paddy rice and table 4.9. for corn and beans. 39 Table 4.8. Surplus of Water per Year for Paddy Rice Planted in Different Months in Transmigration Project of Tajau Pecah Paddy Rice Planted in Months ---------------------------------------- September October November January n positive positive February n n positive March n n n April n n n May n n n June n n n July n n n August n n n September negative n n October negative negative n November positive positive positive December positive positive positive Source : GMU 1978 n : not considered Table 4.9. Surplus of Water per Year for Corn and Beans Cultivation Planted in Different Months in Transmigration Project of Tajau Pecah Corn and Beans Planted in Months ----------------------------------------- Sep Oct March April January n pos n n February n n n n March n n pos n April n n pos pos May n n pos pos June n n pos pos July n n n pos August n n n n September neg n n n October neg pos n n November pos pos n n December pos pos n n Source : GMU 1978 n : not considered 40 4.4. Power inputs availability In the transmigration project of Tajau Pecah, there were three different power inputs used in land preparation (man, animal, and tractor). 4.4.1. Human resource There were 1000 transmigrant families in Tajau Pecah with a total of 4341 people distributed among six village blocks. The block distribution of transmigrant families were as follows block A : 128 families, block B ' 105 families, block C : 192 families, block D : 150 families, block E : 150 families, block F : 175 families. The average for a family was four people, and of a family only 2-3 people were available to work their land (GMU,1978). The field work requirement with hoe and crowbar as tools was measured by local standard, that is 0.25 "borong per kenjing"1 or 692 man hours per hectare (GMU,1978). 1. 1 borong 17 t 17 sq. m 289 sq. meter 1 kejing 5 hours (10000 / (0.25 x 289)) x 5 692 manhour / ha. 0.25 borong / kejing 41 To calculate manhours needed for cultivating different crops in Tajau Pecah, a list of manhour requirements for each activity in every month must be made, and followed by analysis of labor surplus by subtracting the manhour requirements from the availability of manhours. Table 4.10 shows the manhours requirements for one hectare of traditional crops. The availability of manhours is calculated as follows CAP L * H i D I PWD (4.1.) where : CAP available working capacity, manhours / month L = available labor unit, man H = available working hours, hours / day U u available working days, days / month pwd probability of a working day, decimal Table 4.10. will be used in the simulations of labor surplus during growing the traditional crops. Labor surplus of each activity during growing the crops will be obtained by subtracting the labor requirement for each planted crop from the available working capacity of family labor for each month during one year period. The availability of working capacity of a transmigrant family for each month is calculated with equation 4.1. 42 Table 4.10. Distribution of Manhour Requirements per Hectare for Traditional Crops. Months Paddy Rice Corn Beans Cassava Total (h/ha) (h/ha) (h/haI (h/ha) January 180 - - - 180 February 180 398 - - 578 March 380 40 398 25 843 April - 30 40 - 70 May - 240 30 - 270 June - - 210 - 210 July - 20 70 - 90 August - - 70 - 70 September 398 - — - 398 October 70 - - - 70 November 160 - - 60 220 December 180 - — - 180 Total 1548 728 818 85 3,179 Source:GMU 1978 4.4.2. Animal-drawn power Animal-drawn power in Tajau Pecah was derived from Bali cattle (Bos banteng or Bos sondaicus), which were used as a part of the government's "Credit livestock distribution system". The animal-drawn equipment consisted of a locally manufactured plow. Every four transmigrant families received a pair of animals, and the capacity of work of a pair of animals was 140 hour per ha (GMU,1977). 4.4.3. Tractor power Tractors are used to help the transmigrants with the preparation (plowing and harrowing) of their 0.75 ha of crop land. The 0.25 ha of houselot was worked by the transmigrants 43 themselves. The tractor can be rented for Rp.50,000 per ha (Rp is rupiah, Indonesian currency)’. The tractors are used for first and second plowing and harrowing operations. 4.5. Cropping Rotation and The Transmigrants’ Return Present cropping rotation and amount of cultivated areas for Tajau Pecah and the financial analysis of a transmigrant family are shown on tables 4.12. and 4.13. Table 4.11. Present Cropping Rotation and Planted Areas for Different Crops in Transmigration Project of Tajau Pecah No. Crops Months Planted Areas (Ha) 1. Paddy Rice September - 0.70 January 2. Corn May - August 0.18 3. Beans January - 0.18 April 4. Cassava February - 0.35 September Source : GMU 1978 * Exchange rate : US. 1.00 = Rp. 450 (1977) Since 1986 US 8 1.00 = Rp. 1,650 44 Table 4.12. Financial Analysis of a Transmigrant Family Production at the Present Time Items Paddy rice Corn Beans Cassava Planted Area (ha) 0.7 0.18 0.18 0.35 Income : Production (Kg) 1050 144 126 3500 Value (Rp. / Kg) 70 50 100 10 Gross Income (Rp) 73500 7200 12600 35000 Production cost: Fertilizer (Rp) 7000 1800 1800 3500 Seeds (Rp) 1050 2700 1620 - Others (Rp) 32550 672 1143 14700 Total 40600 5172 4563 18200 Net Income (Rp) 22400 2028 8037 16800 Source :GMU 1978 Farmgate price of each traditional crop will be used in the simulation of the financial analysis of the transmigrant family model. Farmgate price of the traditional crop can be found on appendix B. Market price of rice, Rp. 90 per kg milled rice, is used to analyze the rice equivalent for transmigrant family income. Data on this chapter will be used in the analysis of the transmigrant family model on the following chapter. V. MODEL DEVELOPMENT AND SIMULATION INPUTS FOR THE TRANSMIGRANTION FAMILY MODEL 5.1. System Approach for the Transmigration Family Model 5.1.1. Background Information The subsistence level of a transmigrant is used to analyze the total area needed for the farmland of a transmigrant family. The subsistence level is defined as a level at which the basic supply needs of a transmigrant are fulfilled, and it is measured by the equivalent amount of rice production needed for a transmigrant's food and other needs by selling his farm products. The equivalent subsistence level in milled rice was defined to be 240 Kg per person per yearl. If the average size of a transmigrant family is assumed to be five people (MOT, 1978)’, then the equivalent of 1200 kg of milled rice must be obtained by each transmigrant family from their farm during a year. 5.1.2. Problem Definition Research carried out by GMU (1978) showed that the average land area cultivated by a transmigrant family was 1.00 "bau" (local term for 0.7 hectare). This was the area 1 Sajogjo, et a1., 1978 in Penny 1982 1 Ministry of Transmigration 45 46 developed from alang - alang grass. The rest of the area of the allocated two hectares was left uncultivated. The families for which these data were collected did not have power inputs such as animal traction or a tractor to assist with the work. The question arose as to what are the limitations on the productivity of the transmigrant families, and how can they be overcome. A systems model was formulated in this study to analyze the productivity of transmigrant families with various assumed inputs and conditions. A systems approach as a problem analysis methodology is used to analyze and to compare 1. Various areas cultivatable with different power inputs used in land preparation. 2. The transmigrant productivity and return with different crop mixes. 5.1.3. System Identification The principal features for analysis of the transmigration family model are identified and illustrated in figures 5.1. and 5.2. The controllable inputs for this model are the availability of human resources, animals and tractors at the transmigration sites, and the production inputs such as crops, herbicides, and fertilizer. The number of human laborers and power inputs in these controllable inputs may be varied during the simulation process to compare several combinations of inputs. 447 pests diseases cuIIurjaI tine . land -raclnce -uailable °'93'I“9 condlll + + + , . _ work II'IQ - pro. Fern apabl I I- 49°II0" size Iies InpuIs + + > + t o IrsdiIio . "a. anlnal crops IracIor unpuls governmenl Policies Figure 5.1. Causal loop For Ihe Iransnigranl family model I48 environmental controllable inputs : - weather inputs : - pests e diseases - family labor - gov. policies - animal \t/ ‘ IFBCIOF size - land conditions of ; < a farm I II - crops - Fertilizer - herbicides input parameter - Transmigration dev. criteria feedback Figure 5.2. Blackbox diagram For transmigrant family model desired outputs : - maximum productivity - increase in return undesired output : - increase in labor shortage 49 The exogeneous or environmental inputs are variables which affect the system but are not influenced by the system (Manetsch and Park, 1987). In the transmigration family model, environmental inputs were weather conditions, pests and diseases, and established government policies. The input parameters, which are to be fixed during the simulation process, are variables which serve to specify the structure of the system (Manetsch and Park, 1987). At the present time, transmigration development criteria such as an allocation of two hectares of land, selected agricultural equipment for the transmigrants are classified as input parameters. The desirable results from using the transmigration family model were a higher productivity and low cost-return ratios. An decrease of labor capacity would be an undesirable result which would force transmigrants to readjust their management practice. 5.1.4. System Linkage The linkages between identified components in the transmigration family model were illustrated in the causal loop model presented in figure 5.1. The following discussion describes the relationships between the critical components in the system. The problem of labor shortage during land preparation was analyzed by replacing human labor with animal-draft 50 traction or a tractor. Application of a power input reduces the number of laborers needed for land preparation. The land condition, along with the availability of human labor or other power inputs, directly affects the productivity of labor or other power inputs. The land condition after the land clearing operation affects the field efficiency of animals or tractors during land preparation for growing the crops. Cultivated areas were planted with traditonal crops such as paddy, corn, beans, and cassava by the transmigrants. The size of the cultivated area for each crop was determined by the availability of labor from each transmigrant family in the preparation of the land for growing crops and the number of non rainy days during the month of land-preparation operations. Crop selection is based on local soil conditions, weather, and capability of obtaining production inputs. The traditional crops were manipulated in simulation studies to analyze the labor capacity during growing the crops, the productivity of a labor unit, and transmigrant family’s return with various crop mixes. The production inputs remained fixed during the simulation process. 5.2. Transmigration family model The working capability of a transmigrant family and the availability of non-rany days are two critical factors in 51 determining total area cultivatable by the transmigrant families during land preparation. The working capability of a transmigrant family was influenced by the availability of family laborers and other power inputs, and the workability of the soil for land preparation. The availability of non- rainy days are affected by the probability of a working day. To avoid the failure of harvest because of pests and diseases, the transmigrant generally must plant their crops simultaneously with those of other farmers in the surounding area. This situation creates a labor shortage during the land preparation period. Assumed production inputs (crops, herbicides, and fertilizer), which are adapted to the local conditions of soil, pests and diseases, were purchased from a local market. The crops were to be planted on the area cultivated by the transmigrants. The area planted for each crop was adjusted to transmigrant capabilities. Shortages of labor during crop growth is eliminated by rearranging the cropping pattern and reducing the planted area for each crop. Evaluation of the planted area for each crop provided a feedback mechanism for the system. 5.2.1. Farm size analysis. Working capabilities assumed for humans using a hoe and crowbar as tools were taken from measurements GMU (1978). The 52 measured capacity for a person was 0.25 'borong per kejing’ and it was equal to 692 manhours per hectare (see section 4.4.1.). In the evaluation of labor utilization, an assumption was applied to differentiate between men, women, and children. An adult male devoting one hundred percent of his time working in an agricultural field was assumed equal to one unit of labor. This assumption is a modification of data taken by GMU (1978) and TAD (1981). The following table 5.1. shows the composition of a labor unit. Table 5.1. The composition of a unit of labor Types Labor unit Explanatory Adult man 1.0 working 100% of his time in agricultural field Adult woman 0.5 if she has children under seven years old 0.75 if all children are at least seven years old Children 0.30 if in school (seven years 0.50 if not in school and older) Other Adults 1.0 The working capacity available in term of manhours per month was calculated as follows : 53 CAP = L t D t H ! pwd (4.1.) where : CAP 2 available working capacity, manhours / month L = available unit labor, man D = available working days, days / month H = available working hours, hours / day pwd = probability of a working day, decimal The cultivated area was then calculated by dividing the working capacity available to actual capacity as follows : A = CAP / CM (5.1.) where A = cultivable area, hectares CM = measured working capacity 692 manhours / ha, (GMU,1977). Effective field capacity of power input derived from Hunt (1977) was used to calculate the capability of machine operation and animal traction. Effective field capacity was defined as actual rate of performance of land or crop processed in given time based upon total field time (ASAE Standards, 1984). Field operation capacity was calculated as follow EFC: S 'W‘E (5.2.) 10 54 Where : EFC = effective field capacity, Hectares / hour S = speed, Kilometers / hour W = effective width of equipment, meters E = field efficiency, decimal 10 = conversion factor to a unit of Hectares per hour GMU (1978) stated that field efficiency for animal and tractor in the transmigration area was low as the result of land conditions after the land clearing operation. Some stumps were left and pieces of wood could be found in the soil as a result of land clearing operations, makeing power inputs such as animal and tractor difficult to operate in the new area. For the purpose of simulations, field efficiency of power inputs is assumed to be 0.51 - 0.59 (GMU 1978). Area cultivated by animal-drawn traction or tractor were calculated by an equation derived from ASAE Standards (1984) as follows A = EFC t D t H * pwd (5.3.) where A = cultivable area, hectares D = the estimated working days available, days H = the expected hours available for field work each day, hours pwd = the probability of a working day, decimal 55 Several assumptions were made in evaluation of working days and expected working hours available as follows: Working days available for each month were obtained through the evaluation of the average monthly non-rainy days for 25 years (1952 - 1976) in the location (Appendix A). The working days were calculated by multiplying total days in a month to the probability of a working day. A rainy day was defined as a day with rainfall at least equal to 10 mm, thus there would be no work during the rainy days (Djojomartono 1979). The field work would be resumed on the following day if there was no more rain. The probability of a working day (pwd) was obtained from the ratio of total non-rainy days in a month to total days for that month. In this model, soil conditions were not assumed as a constraint since soil can be used to plant the crop for a whole year. An example of a pwd calculation is as follows Month : September Number of non rainy days : 25 pwd = 25 / 30 = 0.83 56 4. The effective working hours in a field were assumed to be 5 - 10 hours per day (Soedjatmiko, 1981), and the transmigrants work longer in the fields during the busy field operation. For instance, during the land preparation operation the working hours were assumed to be ten hours per day, while the manuring operation was assumed at six hours per day. The transmigrants work longer in the field during the wet months to compensate for the rainy days when work could not be accomplished (Appendix B). 5.2.2. Productivity analysis The size of the planted area for each crop was determined by the ability of a transmigrant family to prepare the land for growing each traditional crop. In this model land preparation was carried out during September for rice, February for corn and cassava, and March for beans. Two assumptions were made in the cropping system as follows 1. The applied cropping system was a multiple cropping system defined as growing two or more crops on the same field at different time during a year (FAO 1983). The transmigrant will divide his farm land into several plots depending upon the number of crops he wants to plant and the decision to plant each crop on a different plot. 57 2. Multiple cropping would be specified as relay inter-cropping; that is, growing two or more crops simultaneously during part of each one’s cycle (FAO 1983). A second crop was inter-planted before the first crop is ready to harvest. The planting time used for each crop was taken from the evaluation of crop water requirements and water balance made by GMU (1978). In the transmigrant family model, crops would be planted in the particular month that the availability of water for crops meets or exceeds the water requirement for growing the crops (see tables 4.8. and 4.9.). The following is the timetable used for planting, growing, and harvesting Table 5.2. Timetable for planting, growing, and harvesting traditional crops. No. Crops Months 1. Paddy November - March 2. Corn March — June 3. Beans April - July 4. Cassava March - November The projected yield (see table 3.6.) was used to establish the analysis of the expected production in this model. The expected production was calculated as follows 58 EXPRODI = AI * PROCROPI, (6.4.) where : EXPRODI = Expected production of planted crop, Kg AI = Planted area, hectare PROCROPI = Projected crop yield, Kg / hectare i = Tradional crop, i: 1,2,...,n 1 = paddy rice 2 = corn 3 = beans 4 = cassava The productivity of the transmigrant is defined as the ability of a unit laborer to generate a number of products, and it is analyzed as follows : EXPRODI PROVIi = (5.5) unit labor where : PROVI: = productivity, Kg / unit labor The evaluation of cost and return was done by subtracting the costs of producing each traditional crop from the gross income obtained from selling the crop. The result of the return was analyzed by converting to the milled rice equivalent (EQRICE). The following flowchart is a logical computer program for the transmigration farmland model. . manual labor CPI’ II: CREME L=H*H*C IR: Bitt-IttPIIlI :LIIIK LIP/Cit animal or tractor .____r___, II: EFC*II*H*PI1I figure 5.3. Transmigration family model Flowchart 60 figure 5.3. (conI’ d) IIIUIIE TIE CILTIWBLE IREIIFIIIEIIZHCRIP PRINT /II’ECTE1PROMTIIII7 W735 TOTPLEII’ROB fil- EC PROMIIUITY RICE EllUIlflEIIl 01mm: L: II+ II+C It: llmllml’llll (ZIP: INK ClIS: CIP- Cll mm: mm: PROBIIIxItI’RIII ‘ 1mm; MUDxSEIPRICE mu : lino: - PROSIISI entice: mx PIRPRICE $ I new mm: ’ 01mm: ,mmct, Brion: Item mom, M, 1mm: 2mm PIIIPRICE. men PRDUI: TOIPROII/ L 61 Note on flowchart : H D pwd t" 0 £1 3 CAP CM 10 EFC CAS EXPROD PROCROP TOTPROD availability of working hours, hours / day availability of working days, days / month probability of a working day, decimal availability of working time = H x D t PWD, hours man laborer, man woman laborer, man child laborer, man availability of unit laborer = M + W + C, man availability of working capacity = L 8 Wk, manhours measured capacity = 690 manhours / hectare working speed of a power input, Km / hour effective width of a piece of equipment, meter efficiency, decimal conversion factor to a unit of hectare effective field capacity, hectare / hour number of cultivable areas = CAP / CM or EFC * H t D x PWD surplus of working capacity, manhours expected production of a crop, Kg / ha projected production of a crop, Kg / ha total production of crops, Kg 62 PROVI : productivity of a laborer, Kg / unit laborer PRODIN : production input of each crop, Kg INPRICE : price of input, Rp. PRODCOST : cost of production, Rp. SELPRICE : selling price of a product, Rp. INFLOW : total of production sale. Rp. RETURN : profit of total production, Rp. EQRICE : equivalent of value of rice. Kg 5.3. System Simulation Inputs Simulation usually refers to a computer program or other functioning models that represent a system of different design and management strategies (Manetch & Park 1987). Simulation models are best at providing a range of information rather than a single optimal point (Soedjatmiko 1981). The transmigration family model was formulated to represent the productivity of a transmigrant family. Various assumptions of labor input for the transmigration family model can be made to represent the availability of family labor and outside labor. The model may also be used to consider the use of animals and l or hand tractors. Plans call for the transmigrants to arrive at the new area during the month of August which allows them approximately two months to prepare their land for planting 63 in November. Several simulations were used to analyze the area that the transmigrants could prepare and cultivate. Those simulations were as follows: 1. Simulation I assumed that the land preparation was done entirely by the transmigrant family, and the family consisting of parents with two children under seven years old who were not in school. 2. Simulation 2 assumed a family with one child under seven years old, and one child more than seven years old, but in school. 3. Simulation 3 assumed a family with two children older than seven years old and in school. 4. Simulation 4 assumed that the labor input was the family from simulation 3 plus one hired laborer for land preparation. It was assumed that only manual labor was used for growing the crops on all simulations. The rationale for this is that planter and other agricultural machines are generally not available in transmigration areas; and planting, weeding, and harvesting are done manually. Simulations using additional power inputs such as animals or hand tractors for land preparation operations would be analyzed to find out the affect of using power inputs to the transmigrant family income. 64 Transmigrant family working hours and davs were taken from the file WORKDATA. These assumptions provide the availability of working hours and days based on the‘ probability of each working day in the course of a year. The following table 5.3. shows the simulated availability of labor unit for the land preparation. Table 5.3. Simulated Labor Input Units for Land Preparation (man). Simulations M1 W2 Cu3 Ca‘ Labor unit 1 l 1 0 0 1.5 2 1 1 0 1 1.8 3 1 1 0 2 2.35 4 2 1 0 2 3.35 1. M = man 2. W = woman 3. Cu = children under seven years old 4. Ca children at least seven years old Labor surplus was obtained by subtracting the labor requirement per hectare for growing traditional crops from the monthly availability of labor input beyond the land preparation operation. The labor requirement data are included in file LABDATA. Projected yield per hectare of each traditional crop was used to summarize the expected production from a mixed crop; that is, the traditional crops were assumed to be planted in the same field that consists of several plots. Each plot would be planted with one traditional crop. Projected yield 65 data were taken from the research findings of Gadjah Mada University (1978) and are listed under file PROJCROP. The projected yield per hectare might be higher if land preparation is done using animals or hand tractors (Soedjatmiko 1981). Production costs and the selling prices of products were assumed for a financial analysis of a transmigrant family. The production costs are listed under file PRODCOST and selling prices at farm level (farmgate price) are listed under file PRICEDAT. All these data files are included in appendix B. Each land productivity simulation was run to evaluate the different assumed inputs of manual labor, animals, and hand tractors. A custom hired animal or tractor was assumed along with owning a hand tractor, to examine how they affected a transmigrant’s farm income. VI. SYSTEM SIMULATION OUTPUTS AND DISCUSSION The system simulation outputs of the transmigration family model were; cultivable area of farmland, surplus labor evaluation, transmigrant productivity, and financial analysis. 6.1. Cultivable area analysis Table 6.1. presents the cultivable area results with different assumed labor inputs. Table 6.1. Simulated Size of Cultivable Area With Different Assumed Labor Inputs for The Land Preparation Simulation Area Cultivable (hectare) Paddy rice Corn Beans Cassava Total 1 .54 .15 .37 .15 1.21 2 .65 .19 .44 .18 1.46 3 .85 .24 .57 .24 1.90 4 1.21 .34 .83 .34 2.72 Land preparation for paddy rice was carried out in September. Working hours for land preparation were assumed to be 10 hours per day, while probability of a working day during September was assumed to be 0.83 (Appendix B). Working time available for September (30 days) was found by multiplying the working time during September to probability of a working day in September , 10 t 30 t 0.83, which equals 249 hours per month. Assumed labor inputs consist of one 66 67 man, one woman, _and two children under seven years old (simulation 1). Total labor units available for this simulation is 1.5 man. The area that a transmigrant family can cultivate during September was 0.54 ha of land (249 hours t 1.5 man / 692 manhours per ha). 692 manhours per ha was measured working capacity of one man (see section 4.4.1.). The analysis for other simulations and crops were calculated in the same way. Table 6.1. shows that the cultivable area increases with additional labor units as a small child attains an age more than seven years (simulation 2). The results are a projected increase of 0.25 ha in land utilization. If a transmigrant family has two children over seven years old and in school (simulation 3), the area cultivated is predicted to be 1.90 hectare. With one additional hired laborer (simulation 4), the transmigrant family can expand the farmland utilization to 2.72 hectare; an increase of more than 43 percent above simulation of a family with two children older than seven years old and in school. 6.2. Labor surplus analysis Table 6.2. presents the labor inputs availability for each month during one year of growing traditional crops. In this analysis, assumed labor inputs for each simulation was multiplied by the probability of working time for every month during the year. The probability of working time for growing 68 the crops is listed under file WORKDATA (Appendix B). Table 6.2. Simulated Labor Availability Condition for Each Simulation for Different Assumed Labor Inputs During Growing The Crops (manhours) Simulations Months 1 2 3 4 January 167 200 262 262 February 210 252 329 329 March 251 301 393 393 April 162 194 254 254 May 190 228 297 297 June 197 237 309 309 July 215 258 337 363 August 232 278 363 363 September 374 498 585 585 October 330 396 517 517 November 180 216 282 282 December 179 214 280 280 T o t a 1 2,699 3,286 4,225 4,225 The availability of labor input for simulation of one man, one woman, and two children under seven years old (simulation one) for January can was calculated as follows 1.5 man 1 8 hours i 31 days 1 .45 = 167 manhours The same calculation is used to analyze the availability of labor inputs each month during one year for different simulation for growing the crops. 69 The analysis of labor surplus beyond land preparation was obtained by subtracting the labor requirement for each traditional crop from labor available on table 6.2. and the results of the analysis are shown on table 6.3. Table 6.3. The Labor Surplus Analysis by Months Based on Labor Requirement of Each Simulation During Growing The Crops (manhours) Simulations Months 1 2 3 4 January 81 97 127 62 February 113 135 176 111 March 36 42 55 -89 April 143 171 224 210 May 143 169 223 191 June 119 144 189 134 July 186 223 292 272 August 206 247 323 305 September 374 498 585 585 October 292 351 458 433 November 85 101 132 68 December 85 97 127 62 T o t a 1 1,863 2,275 2,911 2,344 Table 6.3. shows that total surplus labor for one year for all simulations is positive. However, there is one negative value for March of the simulation with additional hired labor. The additional one laborer (simulation 4) allows the preparation of more area than for the other simulations using only family labor. However, a transmigrant family has a 70 problem of caring for all the crops on the additional land prepared during the month of March. To eliminate the labor shortage, the transmigrants may have to reduce the cultivable area or rearrange cropping pattern by dropping one crop. The analysis for eliminating labor shortage by reducing area cultivated and rearranging cropping patterns will be discussed in page 72 of this chapter. The surplus capacity of table 6.3. shows that there was extra time for the transmigrant family to do field work, and the transmigrant family would use their spare time to do clearing operation such as removing stumps or woods that were left in the field. 6.3. Productivity and returns analysis Table 6.4. shows the simulated production of each traditional crop for different assumed labor inputs. Table 6.4. Simulated Production of Each Traditional Crop for Different Assumed Labor Inputs (Kg) Simulations Paddy Corn Beans Cassava 1 810 120 259 1,500 2 975 152 308 1,800 3 1,275 192 399 2,400 4 1,815 272 581 3,400 71 Table 6.4. shows the simulated increase of production for different assumed labor inputs. Increase in production was the result of the increase of area cultivated by the transmigrant family during land preparation. The highest increase in production, more than 120 percent increase for all production, was found for the simulation with one additional outside laborer during the land preparation operation. Productivity of a labor unit was defined as the ability of a labor unit to produce a specified number of traditional crops. The values of the productivity of a unit laborer are shown on table 6.5. Table 6.5. Simulated Productivity of a Unit Labor to Produce Traditional Crops for Each Simulation (Kg/unit labor) Simulations Paddy Corn Beans Cassava 1 540.00 80.00 172.67 1,000.00 2 541.67 84.44 171.11 1,000.00 3 542.55 81.70 169.79 1,021.28 4 772.34 115.74 247.23 1,446.81 Table 6.5. shows that there was an increase of productivity for the simulation with one additional laborer (simulation 4) during the land preparation. This increase in productivity is caused by an increase in production of each traditional crop. 72 Evaluation of financial analysis for each simulation is presented on table 6.6. In this evaluation, the value of rice equivalent was calculated by dividing the net farm income of a transmigrant family by the market price of rice at Rp. 90 per kg (TAD 1978). The net farm income was defined as the benefit to the farmer after substracting the farm production cost from gross farm income. The hired labor cost assumed was at Rp.500 per day which consisted of Rp 350 for field work and Rp 150 for meal (Soedjatmiko 1981). Table 6.6. Simulated Financial Analysis of Transmigrant Family for Each Simulation (Rupiah) Simulations Items 1 2 3 4 Gross Farm Income 151,800 182,445 238,995 341,595 Prod. Cost: Prod. Input 22,517 27,103 35,243 50,592 Hired Labor 0 0 0 44,500 Bullock 0 0 0 0 Hired Tractor 0 0 . 0 0 Owned tractor 0 0 0 0 Net farm income 129,284 155,342 203,752 246,503 Rice Equivalent 1,436.48 1,726.02 2,263.92 2,738.93 (Kg milled rice) Table 6.6. shows that the results for all simulations projected net farm income higher than subsistence level for a transmigrant family of four people which was assumed to be 73 equivalent to 960 kg milled rice. The highest net farm income was gained for a transmigrant family with an additional laborer used in land preparation (simulation 4). The cost of hired labor was covered by a transmigrant's income from selling his farm products. The hired laborer would be paid by the transmigrants after they sold their farm products. Hired labor was used for land preparation during September, February and March, and the total working period for a hired labor was 89 days. Thus, the hired labor cost was Rp. 44,500. During the non-land preparation period, a hired laborer would work outside the farm area. The cost of production was calculated in the file PRODCOST. The data on production input costs per ha of each traditional crop were listed in this file. Production cost for each simulation was the total cost of production of the traditional crops. Simulation with one additional laborer has the highest production cost of Rp.50,592 while a transmigrant family with two small children (simulation 1) has the lowest cost of production at Rp. Rp.22,517. The highest simulated net income with one additional labor at Rp.246,503 was achieved because of a larger area utilized (2.72 ha compared to 1.21 hectare for simulation 1, 1.46 ha for simulation 2, and 1.90 ha for simulation 3). Although all simulations showed the value of rice equivalent to be higher than the subsistence level, there was 74 some labor surplus and a negative value as shown in table 6.3. To utilize all labor more efficiently the mixed crops and areas of traditional crops was adjusted and simulations were run to obtain more optimun results. One simulation assumed a crop mix of paddy, beans, and cassava without corn. The next simulation assumed that paddy rice was not planted. The transmigrant would buy rice from the market after they sell their farm products. For this purpose, corn was planted together with beans and cassava. Tables 6.7. and 6.8. present the timetables for these two simulations. Table 6.7. Timetable for Planting, Growing, and Harvesting Paddy Rice, Beans, and Cassava. No. Crops Months 1. Paddyrice November - March 2. Beans April - July 3. Cassava March - November Table 6.8. Timetable for Planting, Growing, and Harvesting Corn, Beans, and Cassava No. Crops Months 1. Corn October — February 2. Beans April - July 3. Cassava March - November 75 Results of simulation without corn and simulation without paddyrice can be seen on table 6.9. Table 6.9. Results from the Two Simulations Paddy, Beans, Items and Cassava Corn, Beans, and Cassava Cultivatable area (ha) paddy .85 corn . 0 beans .57 cassava .48 Total Farm Production (Kg) paddy 1,275 corn 0 beans 399 cassava 4,800 Productivity (kg/unit labor) paddy 542.5 corn 0 beans 169.79 cassava 2,042.55 No. of month with negative values of 0 labor surplus Financial analysis (Rp.) gross farm income 299,475 production cost 34,994 bullock cost 0 net farm income 264,481 Rice equivalent 2938.68 (Kg milled rice) .85 .57 .48 680 399 4,800 289.36 169.79 2,042.55 244,650 34,216 0 210,434 2338.15 The purpose of the analysis was efficiently during all months and to to utilize labor more eliminate the labor 76 shortage. This analysis assumed that all farm operations were done by the transmigrant family consisting of parents with two children older than seven and in school. The projected area planted for paddy rice, beans, and cassava is 0.85 ha of paddy, 0.57 ha of beans, and 0.48 ha for cassava. These cultivable areas were determined by the working capability of the transmigrant family during land preparation in September, February, and March. By dropping the corn crop from the cropping pattern and reducing the area planted for paddyrice, the problem of labor shortage was eliminated. The total cultivatable area without corn was the same as the previous analysis of a transmigrant family of four, the net farm income of the transmigrant family increased by more than 25 percent. This incremental net income was caused by reduction of production cost of the transmigrant and a 100 percent increase in cassava production. The incremental net income of the rice equivalent also increased from 2,263 Kg to 2,938 Kg or a 30 percent increase. The crop mix without paddy projected a lower rice equivalent of about 20 percent compared to the mixed crop with no corn. The assumed price of corn per kilogram was 28 percent lower than for rice per kilogram, thus it lowered the farm income. The rice equivalent of the crop mix without paddy was 2,338 kg milled rice or almost 144 percent higher than the 77 assumed subsistence level for four people. The shortage of labor during the growing season (March) was also eliminated. 6.4. Analysis of power inputs used in land preparation. The following analysis was intended to study the transmigrant family income that might result from using animal traction and a tractor as power inputs. A crop mix of paddy, beans, and cassava was used for the basic analysis. This cropping pattern was used because this pattern showed that the transmigrant family can utilize the planted area of each crop and there was no labor shortage. The animal traction simulation assumed the use of a moldboard plow with a 0.25 m width and a working speed of 1.22 km per hour (Soedjatmiko 1981). The field efficiency for animal traction was assumed at 0.54 (GMU 1978). The animal was custom hired. For the custom-hired tractor analysis, all data were taken from Soedjatmiko (1981). The hand tractor was equipped with rotary tiller with 20 to 24 blades (54 - 64 cm wide). During the simulation run, a rotary tiller with an assumed 60 cm width was used. The working speed of a tractor was 2.33 km per hour, and the field efficiency was assumed to be 0.64 (GMU 1978). The cost of a custom-hired tractor was Rp. 16,700 per hectare. The equivalent cost for the operator's meal was Rp 900, while cost of the operator itself was included in the cost of the custom-hired tractor. 78 Another simulation assumed that the transmigrant owned a tractor. During the land preparation operation, the transmigrant would hire out his tractor to others. This was done to reduce his cost of ownership. The tractor price was assumed to be Rp 1,650,000. Fuel and oil costs for the tractor were Rp 50 and Rp 500 per liter respectively. Table 6.10. shows the results of analysis using power inputs. Table 6.10. Simulated Result of Assumed Power Inputs Simulations Items animal custom hired owned tractor tractor Financial analysis (Rp.) Revenue gross farm income 299,475 299,475 299,475 Custom hired inc. 0 0 285,570 Total revenue 299,475 299,475 585,045 costs : . production cost 34,994 34,994 34,994 custom hired bullock 45,550 0 0 custom hired tractor 0 33,350 0 fixed cost 0 0 181,500 operating cost 0 0 7,720 owned tractor cost 0 0 189,220 net farm income 218,931 230,951 306,831 Rice equivalent 2,432 2,566 4,009 (Kg milled rice) 79 From the analysis of table 6.10., the bullock as pOwer input costs amounted to Rp. 45,550. These costs consisted of Rp 27,550 cost for land preparation of 1.90 ha and Rp 18,000 for the cost of the operator's meal for 20 days. The bullock power input simulation projected a 12 percent lower net farm income as compared to the simulation of a crop mix with no corn. The rice equivalent for simulation using a bullock was found at 2,432 kg milled rice. The simulation of a custom hired tractor projected a transmigrant’s net income higher than animal traction. The actual net income of a custom hired tractor was Rp 230,951 which was Rp 12,020 higher than for the custom hired bullock. Increases in the transmigrant’s net income were a result lowered operating costs when using a custom-hired tractor compared to a custom-hired bullock. In simulation with a custom-hired tractor, land preparation was done in two days. The cost of land preparation was Rp 31,730 and operator cost was Rp 1,800. The increase of net income of Rp 2,318 was equivalent to 134 kg of milled rice. The simulation of a farmer owned tractor resulted in the highest net farm income of the transmigrant family when compared to other simulations. Net income of the transmigrant with this simulation was Rp 306,831 or equivalent to 4009 Kg milled rice. This projection was the result of additional income the transmigrant received from renting his tractor to other farmers. The cost of ownership or fixed cost of 80 simulation for the transmigrant who owned his own tractor was Rp. 181,500. This ownership cost was covered by renting his tractor to other farmers. Soedjatmiko (1981) in his research found out that tractor owner’s return was almost double from his costs. Simulated owned tractor shows that the transmigrant return from custom work was about Rp 96,000. 7.1. VII. CONCLUSION AND RECOMMENDATION Conclusions Several conclusions can be made from this study and are as follows 1. A system model was developed and tested for productivity of the transmigrant family which provides the means to study productivity and land utilization under various conditions and with different input resources. Simulation studies were made with secondary data pertaining to labor, animal, and tractor inputs and with various resource assumptions. a. A transmigrant family of four with no outside laborers could utilize 1.9 hectare of land with a crop mix of paddyrice, beans, and cassava; or a crop mix of corn, beans, and cassava. b. The hiring of one laborer for land preparation increased the land utilization capability of a transmigrant family to about two hectares based on assumptions made. c. Based on assumptions made, a transmigrant family’s farm income was Rp 218,914 for a custom—hired 81 82 bullock, Rp 230,951 for a custom-hired tractor, and Rp 306,831 for a transmigrant family owned a tractor. 3. The simulation studies made provide examples of how the systems model might be utilized in the planning of land and resource allocation to transmigrant families. 7.2. 83 Recommendations for futher research The data used in the transmigration family model was taken from research carried out by Gadjah Mada University. It is suggested to take direct measurement of manual labor, bullock, and tractor on transmigration sites to improve the model. Futher research on the capability of human labor is needed. To increase the reliability of the model, the capability of a man, a woman, and children need futher development and verification. Futher research on the farm production of different crops using man, animals and tractor is needed to find out the differences in incremental farm production as affected by power inputs used on land preparation. LIST OF REFERENCES Anonymous. Augsburger, Doorenbos, List of References 1973. The Basic Stipulations for Transmigration, Statute No. 3 of The Republic of Indonesia. Department of Man Power and Transmigration. Jakarta, Indonesia. 1978. Prosedur Standard Perencanaan Pemukiman Transmigrasi. Departemen Pekerjaan Umum. Jakarta, Indonesia.(in Bahasa Indonesia). 1978. Pilot Proyek Pengusahaan Tebu Rakyat Dalam Rangka Pemekaran Daerah Pemukiman Transmigrasi Tajau Pecah Kalimantan Selatan. Fakultas Teknologi Pertanian Universitas Gadjah Mada. Yogyakarta, Indonesia. (in Bahasa Indonesia). 1983. Guidelines : Land Evaluation for Rainfed Agriculture. FAO Soil Bulletin, number 52. Food and Agriculture Organization. Rome, Italy. 1984. Agricultural Machinery Management Data. ASAE Standard, ppe 156 - 162e Ste Joseph, Michigan. 1984. Agricultural Machinery Management. ASAE Standard, pp. 296 - 299. St. Joseph, Michigan 1985. Statistical Yearbook of Indonesia, Central Bureau of Statisitcs. Jakarta, Indonesia. Land Clearing. Caterpillar Tractor Co. H.K.M. 1985. Animal-Drawn Equipment in Transmigration Areas. Technical Report. Food and Agriculture Organization. Jakarta, Indonesia. J, and A.H. Kassam. 1979. Yield Response to Water. FAO Irrigation and Drainage Paper. Food and Agriculture Organization. Rome, Italy. and W.O. Pruitt. 1984. Crop Water Requirement. F O Irrigation and Drainage Paper. Food and Agriculture Organization. Rome, Italy. Djojomartono, M. 1979. Simulation to Evaluate Alternative in Post Rice Production. Unpublished Ph.D. Thesis. Michigan State University. East Lansing, Michigan. 84 85 Goldsworthy, Peter R., and N.M. Fisher (Editors). 1984. The Physiology of Tropical Field Crops. John Wiley and Son. New York, New York. Harsh, S.B., L.J. Connor, and G.D. Schwab. 1981. Managing The Farm Business. Prentice-Hall, Inc. Englewood Cliffs, New Jersey. Hunt, Donnell. 1983. Farm Power and Machinery Management, Eighth Edition. Iowa State University Press. Ames, Iowa. Malangkay, R.S.G. 1978. Land Preparation of Settlement Site. Department of Public Work. Jakarta, Indonesia. Manetch, Thomas J., and Gerald L. Park. 1987. System Analysis and Simulation with Application to Economic and Social Systems. Michigan State University. East Lansing, Michigan. Martono. 1985. Panca Matra Transmigrasi Terpadu. The Five Dimensions of Integrated Transmigration. Department of Transmigration. Jakarta, Indonesia. Oldeman, L.R., and M. Frere. 1982. A Study of The Agroclimatology of The Humid Tropics of Southeast Asia. Technical Report. Food and Agriculture Organization. Rome, Italy. Pandya, A.C. 1978. Farm Hand Tools for Transmigration Areas. Food and Agricultural Organization. Rome, Italy. Pelzer, Knut M. 1978. Agriculture : Situation and Possibilities. Transmigration Area Development Report No. 2. Institut fur Wirtschaftsforschung. Hamburg, West Germany. Penny, D.H. 1982. Komersialisasi Pertanian Subsisten : Suatu Kemajuan atau Kemunduran. Bunga Rampai Perekonomian Desa. Sajogjo (Editor). Yayasan Obor Indonesia. Jakarta, Indonesia. (in Bahasa Indonesia). Soedjatmiko. 1981. Choice of Land Preparation for Rice Cultivation in Indonesia. The Utilization of Small Two Wheeled Tractor at The Farm Level in Karawang and Subang Counties in The Wet Season of 1980. Unpublished Ph.D. Thesis. Michigan State University. East lansing, Michigan. Soewardjo, Sumangat, 86 A. 1986. Land Development for Transmigration Areas in Sumatera and Kalimantan. In Land Clearing and Development in The Tropics. R. Lal, et.al. (Editors). A.A. Balkema. Rotterdam, The Netherlands. and T. Purwadi. 1978. Suatu Pendekatan Dalam Penentuan Luas Usaha Tani yang Optimum untuk Daerah Transmigrasi. Agra Ekonomi Mgret 1978. Departemen Ekonomi Pertanian, Fakultas Pertanian, Universitas Gadjah Mada. Yogayakarta, Indonesia. (in Bahasa Indonesia). Swasono, Sri-Edi. 1985. Kependudukan, Kolonisasi, dan Yevjevich, Transmigrasi. Sepuluh Windu Transmigrasi di Indonesia 1905 - 1985. Swasono and M. Singarimbun (Editors). Universitas Indonesia Press. Jakarta, Indonesia. Vujica. 1972. Probability and Statistics in Hidrology. Water Resources Publications. Fort Collins, Colorado. APPENDIX A APPENDIX A Appendix A consists of rainfall and rainy days data for transmigration sites of Tajau Pecah. This monthly data was taken by Gadjah Mada University when they did research on the transmigration program in Tajau Pecah. The rainfall data were taken for the years 1952 - 1976. 87 Sept. October Move-b. M. July Regent “..-...o... ......u.. ..--.. «a... “...-......_- “M“..-m Jme nag Feb. W Mil Distribution of rainfall and rainy days Pleihari, South Kalimantan, 1952 - 1976 Jeni-‘9 W11: 11 Yet 88 '2“ is aa ea as as as a" ea r= aa as e2 a= 2= 22 an as e= e= s= a! :2 as a! e' e8 3“ gs gr g: 5: g: s' g: a" -" g' g: n: as e- re 8' gr so en °° §- n' a“ z- n" °° 32 0° 3' a~ g2 52 a“ g: as =* as ~~ a" -~ °° °° a: a“ as as 5“ a: a: a* 3* ~~ 2° °° ¢~ e- s" a“ go gs 32 s" a“ 32 "N s: gr °° gm 8' =° as as 5. £2 e2 is 32 e2 i“ 5“ 8° 2' a: a° as a: s: e“ as as as e2 a: a: 8' e: a* 22 as aa a! ta ta ta ta 92 8° e2 a“ x2 t! 314 1? 20? 20 262 13 343 16 111 19 $4 1? 3” 21 178 1? 2m 14 an 11 3” 19 32 15 256 13 192 11 474 is 316 so 253 19 313 573 1? 562 19 27’ so 33 20 33 21 5. 16 $1 22 $13 20 210 12 260 12 :1 I3 :1 t3 :3 :3 :3 :3 :1 e3 :3 I1 I? 11 E 3 1 3 Q E 3 E 3 i 3 3 1 3 476 319 12 Win a (ceret'd) 1&6 89 165 B 515 15 597 16 594 21 so: 16 226 10 370 12 20 12 274 6 125 20 9791 04 392 16 169 6 in 7 as m an 9 an a an .5 a” 7 an m an M an n we a lan an an a n4 6 8' g” at 3° g: a" as 52 §2 g: i5 5° 8“ DO 8'- QN Eh £15 99 £0 :2 £2 .8.“ £5 all g' 8- IN? 5" gm g0 00 £2 81'" £0 01- 5.8. I“ 3"! cm cf) 375 as 81') 2" £2 is fill 130 fig ER 3'? EV. gt. 8" £0 E' 051$ g2 36 EN 82 gg £0 81"! 2° e“ a“ as 2' 8' as e“ e= 8“ gr 22 8' aa :a as a: as ea 5° £2 a! a: as as a“ is m an n an n so u an 14 in u an n we n «n m 2a 9 run an an 14 n3 5 379 10 M 16 210 9 us a an u an e an s 20 w as m an an 28 u in 4 E“ 299 12 433 16 33 16 229 15 01 15 9“ 15 2C 7 215 7 954 21 522 1 1 969 41 1 376 16 119 5 13 13 I? 16 13 13 16 I? I! 13 I: I? 13 212§§E§§§§§3a “m-m’---- .. ... -‘3 r Meteor-0109‘ station, Stung Mti in GMU (1978) Source: CV (Z) APPENDIX B APPENDIX B Appendix B consists of five files that were used in the transmigration family model. Data used for this model was taken mainly from research carried out by Gadjah Mada University of Yogyakarta in 1978. 90 91 Table 1.B. Filename : WORKDATA Months Hours Days PWD 1 8 31 .45 2 7 28 .57 3 7 31 .51 4 6 30 .60 5 6 31 .64 6 6 30 .73 7 6 31 .74 8 6 31 .81 9 6 30 .83 10 6 31 .68 11 7 30 .50 12 8 31 .45 Table 2.3 Filename : LABDATA Months Paddyrice Corn Beans Cassava 1 180 . 0 0 0 2 180 398 0 0 3 380 40 398 25 4 0 30 40 0 5 0 240 30 0 6 0 0 210 0 7 0 20 70 0 8 0 0 70 0 9 398 0 0 0 10 70 0 0 0 11 160 0 0 60 12 180 0 0 0 92 Table 3.8. Filename : PROJCROP Crops Kg / hectare Paddyrice 1500 Corn 800 Beans 700 Cassava 10000 Table 4.B. Filename : PRODCOST Cost (RP. / ha) Items Paddyrice Corn Beans Cassava Fertilizer 10,000 10,000 10,000 10,000 Seeds 1,500 15,000 9,000 0 Others 46,500 3,735 6,352 42,000 Table 5.3. Filename : PRICEDAT Crops Price (Rp / Kg) Paddyrice ‘70 Corn 50 Beans 100 Cassava 10 APPENDIX C APPENDIX C Appendix C consists of a computer program for the Transmigration Family Model. This program was written in BASIC language using QUICKBASIC of MICROSOFT. 93 94 ’Hari Respati ’Farmsize Model for Transmigration Program ’A MS Thesis ’June 30, 1988 1 ’*¥¥*******#*8*****t*tttitt$¥¥t¥¥¥¥**¥¥*****¥***********¥*¥* COLOR 3, 0 DIM m$(12), CAP(12, 4), crop$(4), crop(4), projcrop(4), prod(4), item$(3) m$(1) = "January " m$(2) = "February " m$(3) = "March " m$(4) = "April " ”3(5) : "May ee m$(6) = "June " m$(7) = "July " m$(8) = "August " m$(9) = "September " m$(10) = "October " m$(11) = "November " m$(12) = "December " crop$(1) = "Paddy " crop$(2) = "Corn " crop8(3) = "Beans " crop$(4) = "Cassava" item$(1) = "Fertilizer" item$(2) = "Seed " item$(3) = "Others " ttttttitttt3*88833418883388t888**tt*33833!**3**#38*****¥3¥*X CLS PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT 1' 11 " 4* A SYSTEMS MODEL ANALYSIS OF TRANSMIGRATION it" " 8113133 FAMILY PRODUCTIVITY AND RETURNS 8388*!" -- a computer program -- H H M H H fl '1 N " June 30, 1988" East Lansing, Michigan" 95 PRINT "" PRINT PRINT "" PRINT "" flos = "scrn:" GOSUB getkey ’3*888$8#8818!338883883!88*8888888338tttittttttitttttttttt MainMenu: CLS LOCATE 8 PRINT " PRINT PRINT " PRINT "" PRINT " PRINT "" PRINT " PRINT " " PRINT " PRINT PRINT INPUT " IF Choice = 1 THEN GOTO StartLabor ELSEIF Choice = 2 THEN GOTO StartPower ELSEIF Choice = 3 THEN GOTO LaborData 883*38438 ELSEIF Choice = 0 THEN GOTO tamat END IF BEEP GOTO MainMenu M A I N M E N U #838183!!!" [1] Manual Labor Land Preparation" [2] Power Input Land Preparation" [3] Labor Surplus Calculation" [0] Exit" Your Choice : , Choice ’4*3*1*883388821*8838818#8888338181388883838338318883383888 StartLabor: CLS PRINT PRINT PRINT PRINT INPUT '9" mo INPUT PRINT INPUT "tutti: Manual Labor Land Preparation 3:88:33!" "Basic information:" "When do you start preparing the land (Jan=1)"; "How many men are available to work"; man "Is there any woman working in land preparation"; jwbt IF jwb$ = "yes" on jwb’ = "YES I! OR jwb’ = "Y" OR jwbs 96 = n yer THEN GOTO woman ELSEIF jwbs = "no" OR jwbs = "No" OR jwbs = "NO" OR jwbs = "n" OR jwbs = "N" THEN wc = 0 wcs = 0 GOTO children END IF woman: PRINT "" PRINT "Woman worker information:" INPUT "How many women have children under seven years old "; wc PRINT "(Write 0 for next question if you've answered the above question)" INPUT "How many women have children more than seven years old"; wcs children: PRINT "" INPUT "Are there any children working in land preparation"; jwb$ IF jwb$ = "yes" OR jwbs = "YES" OR jwb$ = "Y" OR jwbs = n y n THEN GOTO ChildrenCalculation ELSEIF jwbs = "no" OR jwbs = "No" OR jwb$ = "NO" OR jwbs = "n" OR jwbs = "N" THEN cs = 0 one = 0 GOTO continue END IF ChildrenCalculation:, PRINT "" PRINT "Children workers information:" INPUT "How many children go to school"; cs INPUT "How many children do not go to school"; cns continue: PRINT "" INPUT "What is file name for WORKing DATA"; FWORKDATAS PRINT "" OPEN FWORKDATAS FOR INPUT AS #2 00303 GetOutput LaborCalculation: wl = wc * .5 w2 = wcs * .75 wt = wl + w2 cl c2 ct L LaborPrint: PRINT CLS PRINT PRINT PRINT PRINT PRINT PRINT FOR I NEXT #1, #.## PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT GOSUB PRINT PRINT CAP area unare PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT cs 8 cns * cl + #1, #1," month) #1, 97 .3 .5 02 man + wt + ct 11 '1 tutti Working time available (hours 8*!!!" 11 11 per #1,":----------------_--__________g __________ :. #1," #1," l I month hours ,days pwd TO mo INPUT #2, H, D, PWD WK I USING ": #1,": --------------------------------------- : #1, #1, #1, #1, #1, #1, #1, #1, H t D * PWD \ ### 111311110) 9 \ H, D, USING "I ##### I getkey #1, #1, L x a #1, #1, #1, #1," #1," #1, #1, #1, #1, #1, #1, WK CAP / 690 2 - area "tutti Total labor unit available I Man Woman Children 1 ____________________________________ USING "I ## ##.## ##.## ##.## ct, L man, wt, "ttttt Total area cultivable 8113*" #3833" " ' --------------------------------------- ' '. Total labor unitl" #1,": --------------------------------------- :ee #1," #1, :Working capacity Area cultivable .ee Area uncultivable . "I(manhours / month) (ha) (ha) #1,": --------------------------------------- :01 PRINT PRINT PRINT PRINT PRINT CLOSE GOSUB 98 #1, USING ": unarea #1,": --------------------------------------- I" #1, #1, #1, ##### ##.## #.##I"; CAP, area, getkey GOTO MainMenu ’14**¥*********¥#**¥*¥*********¥***¥¥***¥¥**¥*t**** StartPower: CLS PRINT "##3##: Power Input Land Preparation tttxtxtt" PRINT "" PRINT "Basic information:" PRINT "" INPUT "When do you start preparing the land (Jan = 1)"; mo INPUT "What is your animal or tractor working speed (km / hour)"; 8 INPUT "What is the width of your plow or rotary tiller (meter)"; w INPUT "What is the field capacity of your work (0 - 1)"; eff PRINT "" INPUT "What’s the file name for WORKing DATA"; FWORKDATAS PRINT "" OPEN FWORKDATAS FOR INPUT AS #2 GOSUB GetOutput PowerCalculation: EFC = PowerPrint: CLS PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT PRINT #1, (s * w 1 eff) / 10 #1, #1, Her #1, " 8181* Effective capacity ##3##" #1, #1,": ---------------------------------------- :" #1, ": Speed Width Efficiency Effective Capacity I" #1, ": (km/hour) (meter) (decimal) (hectares / hour) I" #1, "I --------------------------------------- :" USING "I ##.## ##.## #.## ###.## s, w, eff, EFC PRINT PRINT PRINT PRINT PRINT GOSUB PRINT CLS PRINT PRINT PRINT PRINT PRINT PRINT #1, PRINT PRINT PRINT PRINT PRINT PRINT #1, PRINT PRINT CLOSE GOSUB USING "I \ \ USING "I 99 #1, "g --------------------------------------- I" #1, #1, getkey #1, #1, #1, N #1, #1, "g ------------------------------------- I" #1, "I Month Eff. Cap. (Ha/hour) hours Days PWD I" #1, "g ------------------------------------- I" FOR I = 1 TO mo INPUT #2, H, D, PWD area = EFC * H 8 D 8 PWD unarea = 2 - area 133*! Area cultivable 813*3" NEXT I ###.## ## #.## I"; m$(mo), EFC, H, D, PWD #1, u: ------------------------------------- I" #1, #1, #1, re: ------------------------------------ I" #1, "I Area cultivable (Ha) Area uncultivable (Ha) I #1, re: ------------------------------------ :" #####.## ####.## I"; area, unarea ## #1, #1, getkey GOTO MainMenu ’333314338388838!I383881383183382888338tittt¥¥¥¥83¥¥¥¥8¥¥¥ LaborData: ' CLS PRINT "" PRINT "titttLabor Surplus Calculation ¥******¥¥¥**" PRINT "" PRINT "" PRINT " Planted area information:" INPUT "How many hectares of paddy rice do you want to plant "; crop(l) INPUT "How many hectares of corn do you want to plant"; crop(2) INPUT "How many hectares of beans do you want to plant"; crop(3) INPUT "How many hectares of cassava do you want to 100 plant"; crop(4) PRINT "" PRINT " Labor input information:" INPUT "How many men are available in the planting operation"; man PRINT "" INPUT "Is there any woman working in the planting operation"; jwb$ IF jwbt = "yes" OR jwbs = "YES" OR jwbs = "Y" OR jwbs = ee yer THEN GOTO WomanInfo ELSE GOTO ChildInfo END IF WomanInfo: PRINT "" INPUT "How many women have children under seven years old"; wc INPUT "How many women have children more than seven years old"; wcs ChildInfo: PRINT "" INPUT "Is there any child working for planting operation"; jwbs IF jwbs = "yes" OR jwbs = "YES" OR jwbs = "Y" OR jwb$ = n y n THEN GOTO ChildAsk ELSE GOTO continuel END IF ChildAsk: PRINT "" INPUT "How many children go to school"; cs INPUT "How many children do not go to school"; cns PRINT "" continuel: PRINT "" PRINT "Data file information:" INPUT "What is the filename for WORKing DATA"; FWTS INPUT "What is the filename for LABor DATA"; FLB: PRINT "" OPEN FWTS FOR INPUT AS #2 OPEN FLBS FOR INPUT AS #3 GOSUB GetOutput LaborInputCalc: m = man i 1 woman = (wc * .5) + (wcs I .75) 101 children = (cs * .3) + (cns t .5) L = m + woman + children LaborInputPrint: PRINT PRINT PRINT PRINT CLS PRINT #1, "" PRINT #1, " ##1## Labor unit available tittt" PRINT #1, PRINT #1,": --------------------------------------- :" #1, USING "I available man : ###.## I"; m #1, USING "I available woman ###.## I"; woman #1, USING "I available children:###.##I"; children PRINT #1, "I -------------------------------------- I" #1, USING "I Total labor unit available : ####.## man I"; L PRINT #1,"I --------------------------------------- I" PRINT #1, "" PRINT #1, "" PRINT #1, "" PRINT #1, "" GOSUB getkey ManhourPrint: PRINT #1, " ***** Manhours available (manhours) *****" PRINT #1, "" PRINT #1, "I --------------------------------------- I" PRINT #1, "I Month Paddy rice Corn Beans Cassava I" PRINT #1, USING "I###.## ha ###.## ha ###.## ha #.## ha I"; crop(l), crop(2), crop(3), crop(4) PRINT #1, "I --------------------------------------- I" FOR I = 1 TO 12 INPUT #2, H, D, PWD PRINT #1, ": "; msill; FOR j = 1 To 4 NR = H x D x PWD CAP(I, j) = L x WK * crop(J) PRINT #1, USING " #####"; CAP(I. 5); NEXT j PRINT #1, " :" NEXT I PRINT #1, "I ....................................... ;" PRINT #1, "" PRINT #1, "" PRINT #1, "" GOSUB getkey LaborSurplusPrint: 102 PRINT #1, "" PRINT #1, "xxxxx LABOR SURPLUS CONDITIONS tttxt" PRINT #1, " ( mnahours)" PRINT #1,": ---------------------------------------- I" PRINT #1, "I MONTHS CAPACITY LABOR REQUIREMENT SURPLUS I" PRINT #1, "I --------------------------------------- I" TotalCapMonth = 0 TotalLaborReq = 0 TotalSurplus = 0 FOR I = 1 TO 12 LaborReq = 0 TotalCapCrop = 0 FOR j = 1 TO 4 INPUT #3, ln LaborReq = LaborReq + crop(j) t In TotalCapCrop = TotalCapCrop + CAP(I, j) NEXT j Surplus = TotalCapCrop - LaborReq PRINT #1. USING "I \ \ ##.### e#.### ### I": mslI). TotalCapCrop, LaborReq, Surplus TotalCapMonth = TotalCapMonth + TotalCapCrop TotalLaborReq = TotalLaborReq + LaborReq TotalSurplus = TotalSurplus + Surplus NEXT I PRINT #1,": ----------------------------------- I" PRINT #1, USING "I Total : ##,### ##,### ##,### I"; TotalCapMonth, TotalLaborReq, TotalSurplus PRINT #1, "I ----------------------------------- I" CLOSE GOSUB getkey GOTO ProdFin ’*tt*8ttt*¥*833388883338388128*333811883381338888133888i ProdFin: CLS PRINT "P R O D U C T I O N A N D F I N A N C I A L" PRINT " A N A L Y S I S" PRINT "" PRINT "[1] Production and Productivity Analysis" PRINT "[2] Production Cost Analysis" PRINT "[3] Profit Analysis" PRINT "" PRINT " " PRINT "" PRINT "" PRINT PRINT 103 GOSUB GetOutput FProerops = "a:projcrop" FProdCosts = "a:prodcost" FWORKDATAS = "a:workdata" FPriceData$ = "a:pricedat" OPEN FWORKDATA$ FOR INPUT AS #2 OPEN FProerops FOR INPUT AS #4 OPEN FProdCosts FOR INPUT AS #5 OPEN FPriceDatas FOR INPUT AS #6 CLS PRINT PRINT PRINT PRINT PRINT PRINT PRINT INPUT INPUT INPUT PRINT PRINT ’*ttl8*!t8883*88338!1833*32838888388838883833881 productionAnalysis: " 313*! PRODUCTION AND PRODUCTIVITY *****" " xxtxx ANALYSIS xxxxx" "Basic information:" "What is data file for PROJected CROP"; files "What is the file name for PRODuction COSTs"; as "What is the file name for PRICE DATa"; F3 11 N ProductionPrint: CLS PRINT #1, "" PRINT #1, PRINT #1, "Farm Production of a Transmigrant Family " PRINT #1, " " PRINT #1,": ------------------------------- I" PRINT #1, "I Crops Planted Area Production Productivity I" PRINT #1, "I (hectare) (kilogram) (Kg/unit labor) I" PRINT #1, "I ------------------------------ I" Totprod = 0 FOR I = 1 TO 4 PRINT #1, USING "I \ INPUT #4, projcrop prod(I) = crop(I) 1 projcrop Provi = prod(I) / L \ ##.### crop$(I), ###.### ####.##I"; crop(l), prod(I), Provi NEXT I PRINT #1, PRINT PRINT PRINT 104 #1, #1, #1, GOSUB getkey ’8*X#32I3883888813*3833888888883838323383888838388833323 ProductionCostAnalysis: CLS PRINT PRINT PRINT PRINT PRINT #1. "¥**¥* Production Costs Analysis tits!" #1. " (Rupiah) " #1, "H PRINT #1, ":---f -------------------------- :" PRINT #1, "I Items Paddy Corn Beans Cassava I" PRINT #1, "I ............................... g" #1, USING "I Planted area (Ha) : #.## #.## #.## #.##I"; crop(l), crop(2), crop(3), crop(4) PRINT #1, "I -------------------------------- :" Totprod = 0 FOR I = 1 TO 3 PRINT #1, "I "; item$(I); " "; FOR j = 1 TO 4 INPUT #5, prodcost item = crop(j) * prodcost Totprod = Totprod + item PRINT #1, USING " ###,### "; item; NEXT j PRINT #1, " I" .NEXT I PRINT #1, I ------------------------------- I" #1, USING "I Total production costs (Rp): ##yt##p###ot#:"; TOtprOd PRINT #1, "I- ----------------------------- :" GOSUB getkey ’It#3384384!*33!!**8¥**8**8¥8***¥ PowerInputCost: CLS PRINT " 3383* COST OF POWER INPUT ##3##" PRINT "" PRINT " [1] Manual Labor Power Input" PRINT " [2] Bullock Power Input" PRINT " [3] Tractor Power Input" PRINT " [4] Own Tractor" PRINT "" PRINT " [0] No Power Input" PRINT 105 PRINT ' INPUT " Choose Power Input (1,2,3,4 or 0) ", jwb MCost = 0 BLCost = 0 TRCost = 0 IF jwb = 1 THEN GOTO ManualCost ELSEIF jwb : 2 THEN GOTO bullockcost ELSEIF jwb = 3 THEN GOTO tractorcost ELSEIF jwb = 4 THEN GOTO OwnTractor ELSEIF jwb = 0 THEN GOTO ProfitAnalysis ELSE BEEP GOTO PowerInputCost END IF ’3333 CALCULATION OF POWER INPUT COST **** ManualCost: CLS PRINT "" PRINT "Basic information for hired labor:" PRINT "" INPUT "How many hired laborer are used in farm work"; a INPUT "When is hired labor used (Jan = 1)"; mo INPUT "How many Rupiah is the labor cost per day"; CD INPUT "How many rupiah is the cost of the meal per day"; CM FOR I = 1 TO mo INPUT #2, H, D, PWD NEXT I TOTCROP = crop(l) + crop(2) + crop(3) + crop(4) CAP = a 3 H 3 D 3 PWD MCost = (CD + CM) 3 (TOTCROP 3 690) / (CAP / D) GOTO ProfitAnalysis bullockcost: CLS PRINT "" PRINT "Basic information for bullock operation:" PRINT "" INPUT "When is a hired bullock used (Jan=1)"; mo INPUT "How many rupiah for a custom hired for bullock"; RP 106 INPUT "How many rupiah is the cost of the operator’s meal"; CM CLOSE #2 OPEN FWORKDATAS FOR INPUT AS #2 FOR I = 1 TO mo INPUT #2, H, D, PWD NEXT I TOTCROP = crop(l) + crop(2) + crop(3) + crop(4) TempVal = 6 / (TOTCROP / EFC) IF TempVal = INT(TempVal) THEN WorkDays = TempVal ELSE WorkDays = INT(TempVal) + 1 END IF BLCost = (RP 3 TOTCROP) + CM 3 WorkDays GOTO ProfitAnalysis tractorcost: CLS PRINT "" PRINT "Basic information for tractor custom hired:" PRINT "" INPUT "When is a custom hired tractor used (Jan = 1)"; mo INPUT "How many rupiah for a custom hired tractor per hectare"; RP INPUT "How many rupiah is the operator’s meal"; CM CLOSE #2 OPEN FWORKDATA: FOR INPUT AS #2 FOR I = 1 TO mo INPUT #2, D NEXT I CLOSE #2 TOTCROP = crop(l) + crop(2) + crop(3) + crop(4) TempVal = 12 / (TOTCROP / EFC) IF TempVal = INT(TempVal) THEN WorkDays = TempVal ELSE WorkDays = INT(TempVal) + 1 END IF TRCost = (TOTCROP / RP) + CM 3 WorkDays GOTO ProfitAnalysis OwnTractor: PRINT "" PRINT "Basic information for Own Tractorz" PRINT "" 107 INPUT "When is the tractor used "; mo INPUT "What is the purchase price of your tractor"; TRp INPUT "What is the diesel fuel price per liter "; FRp INPUT "What is the oil price per liter"; ORP INPUT "What is the operator’s wage per day"; WRp ’3333333333 ’ TAXES, HOUSING, AND INSURANCE FOR A TRACTOR WILL BE ASSUMED ’ 2 X OF TRACTOR’S PURCHASE PRICE (ASAE STANDARD 1984) ’ FUEL CONSUMOTION (FCOST) AVERAGE IS 1.2 LITERS / HOUR ’ OIL CONSUMPTION (OCOST) AVERAGE IS 0.042 LITERS / HOUR ’ OPERATOR WAGES (LCOST) AVERAGE IS RP.500 PER DAY ’ REPAIR AND MAINTENANCE COST (RMCOST) IS ASSUMED 1.2 % PER 100 HOURS WORK TIMES 90 X OF THE PURCHASE PRICE ’ (TAKEN FROM SOEDJATMIKO 1981) ’333333333333 FixCost = TRp - (.1 3 TRp) / 10 + (.02 3 TRp) CLOSE #2 OPEN FWORKDATAS FOR INPUT AS #2 FOR I = 1 TO mo INPUT #2, D NEXT I CLOSE #2 TOTCROP = crop(l) + crop(2) + crop(3) + crop(4) TempVal = 12 / (TOTCROP / EFC) IF TempVal = INT(TempVal) THEN WorkDays = TempVal ELSE WorkDays = INT(TempVal) + 1 END IF FCOST = 1.2 3 LRp 3 (TOTCROP / EFC) OCOST = .042 3 ORP 3 (TOTCROP / EFC) RMCOST = (.012 / 100) 3 (TOTCROP / EFC) 3 .9 3 PRp LCOST WCOST 3 WorkDays OpCost FCOST + OCOST + RMCOST + LCOST OwnCost = FixCost + OpCost 108 ’333333333333333333333333333333333333333333333333333333333 ProfitAnalysis: CLS PRINT #1, "" PRINT #1, " 33333 Profit Analysis 3333*" PRINT #1, "" PRINT #1, "I --------------------------------------- I" PRINT #1, "ICrops Production (Kg) Revenue (Rp) I" PRINT #1, "I --------------------------------------- I" TotRevenue = 0 FOR I - 1 TO 4 INPUT #6, pricedat Revenue = prod(I) 3 pricedat TotRevenue = TotRevenue + Revenue PRINT #1, USING "I \ \ ###,### ###.### I"; crop3(I). prod(I), Revenue NEXT I PRINT #1, "I --------------------------------------- I" PRINT #1, USING "I Total Revenue (Rp): ###,###.### I" ; TotRevenue PRINT #1, "I ----------------------- I" PRINT #1, USING "I Total Production Cost (Rp): ###,###,### I"; Totprod PRINT #1, USING "I Manual Labor Cost (Rp): ###,###,### I" ; MCost PRINT #1, USING "I Bullock Cost (Rp): ###,###,### I"; BLCost PRINT #1, USING "I Tractor Cost (Rp): ###,###,### I"; TRCost PRINT #1, USING "I OwnTractor (Rp) :###,### I"; OwnCost Profit = TotRevenue - Totprod - MCost - BLCost - TRCost - OwnCost PRINT #1, "I -------------------------------------- I" PRINT #1, USING "I Profit (Rp): ###,### I"; Profit PRINT #1, "I -------------------------------------- I" RiceEquivqlent = Profit / 150 PRINT #1, USING "I Rice Equivqlent (Kg) : ##,###.## I" ; RiceEquivqlent PRINT #1, "I -------------------------------------- I" CLOSE GOTO akhir GetOutput: INPUT "Where do you want the result to be printed (1: screen, 2: printer or 3: file)"; result IF result = 1 THEN 109 flos = "scrn:" ELSEIF result = 2 THEN flos = "lpt1:" ELSEIF result = 3 THEN INPUT "What’s the filename"; flos ELSE BEEP GOTO GetOutput END IF OPEN flo$ FOR OUTPUT AS #1 RETURN getkey: IF flos = "scrn:" THEN LOCATE 25, 20 PRINT "Strike Any Key to Continue "; Colek$ = "" GetKeyO: Colek$ = INKEYS IF Colek$ = "" THEN GOTO GetKeyO END IF RETURN akhir: INPUT "Do you want to reanalyze again"; jwbs IF jwb$ = "yes" OR jwb$ = "YES" OR jwb$ = "Y" OR jwbs = eeyee THEN GOTO MainMenu ELSE GOTO tamat END IF tamat: END APPENDIX D APPENDIX D Appendix D consists of an example of computer program of A SYSTEMS MODEL ANALYSIS OF TRANSMIGRATION FAMILY PRODUCTIVITY AND RETURNS. This example was taken from simulation five of chapter five. 110 111 A SYSTEMS MODEL ANALYSIS OF TRANSMIGRANT FAMILY PRODUCTIVITY AND RETURNS A COMPUTER PROGRAM 112 33333333 M A I N M E N U stresses [11 Manual Labor Land Preparation [2] Power Input Land Preparation [3] Labor Surplus Calculation 10] Exit Your Choice : 113 BASIC INFORMATION : WHEN DO YOU START PREPARING THE LAND ? HOW MANY MAN IS AVAILABLE TO WORK ? IS THERE ANY WOMAN WORKING FOR LAND PREPARATION ? HOW MANY WOMEN HAVE CHILDREN UNDER SEVEN YEARS OLD ? HOW MANY WOMEN HAVE CHILDREN OLDER THAN SEVEN YEARS OLD ? IS THERE ANY CHILD WORKING FOR LAND PREPARATION ? HOW MANY CHILDREN GO TO SCHOOL ? HOW MANY CHILDREN NOT GO TO SCHOOL ? 114 OUTPUT OF MANUAL LABOR LAND PREPARATION : CROP : CASSAVA MONTH : FEBRUARY WORKING HOURS : 10 HOURS WORKING DAYS : 28 DAYS P W D : 0.50 WORKING TIME AVAILABLE : 140 HOURS LABOR UNIT AVAILABLE : 2.35 MAN WORKING CAPACITY : 329 MANHOURS AREA CULTIVABLE : 0.48 HECTARE 115 333 LABOR ANALYSIS FOR GROWING THE CROPS 333 BASIC INFORMATION OF PLANTED AREA : HOW MANY HECTARES OF PADDY RICE DO YOU WANT TO PLANT ? 0.85 HOW MANY HECTARES OF CORN DO YOU WANT TO PLANT ? 0 HOW MANY HECTARE OF BEANS DO YOU WANT TO PLANT ? 0.57 HOW MANY HECTARES OF CASSAVA DO YOU WANT TO PLANT ? 0.48 116 BASIC INFORMATION ON LABOR INPUTS : HOW MANY MAN IS AVAILABLE FOR PLANTING ? 1 IS THERE ANY WOMAN AVAILABLE FOR PLANTING OPERATION ? YES HOW MANY WOMEN HAVE CHILDREN UNDER SEVEN YEARS OLD ? 0 HOW MANY WOMEN HAVE CHILDREN OLDER THAN SEVEN YEARS OLD ? 1 IS THERE ANY CHILD AVAILABLE FOR PLANTING OPEARTION ? YES HOW MANY CHILDREN GO TO SCHOOL ? 2 HOW MANY CHILDREN NOT GO TO SCHOOL ? 0 117 LABOR SURPLUS ANALYSIS (MANHOURS) MONTHS CAPACITY REQUIREMENT SURPLUS JAN 280 153 127 FEB 329 153 176 MAR 393 335 58 APR 254 23 231 MAY 297 17 280 JUN 309 122 189 JUL 338 41 297 AUG 363 41 323 SEP 585 0 585 OCT 517 60 458 NOV 282 165 117 DEC 280 153 127 118 PRODUCTION AND FINANCIAL ANALYSIS [1] PRODUCTION AND PRODUCTIVITY ANALYSIS [2] PRODUCTION COST ANALYSIS [3] NET FARM INCOME ANALYSIS 119 FARM PRODUCTION ANALYSIS : CROPS AREA PRODUCTION PRODUCTIVITY ha kg kg/ unit labor PADDY 0.85 1,275 542.55 CORN o o o ; BEANS 0.57 399 169.79 5 CASSAVA 0.48 4,800 2,042.55 PRODUCTION COST ANALYSIS (RUPIAH): ITEMS PADDY CORN BEANS CASSAVA FERTILIZER 8,500 0 5,700 4,800 SEEDS 1,275 0 5,130 0 OTHERS 3,953 0 3,621 2,016 T O T A L : 34,994 120 FINANCIAL ANALYSIS (RUPIAH) : ITEMS Revenue : PADDY CORN BEANS CASSAVA T O T A L PRODUCTION COST MANUAL LABOR COST BULLOCK COST TRACTOR COST COST OF OWN TRACTOR PROFIT RICE EQUIVALENT (KG MILLED RICE) 95,625 0 59,850 144,000 299,475 34,994 0 0 0 0 264,481 2,938.68 HICI-II llillllllli