Jurnal Bina Praja 9 (1) (2017): 1-13 Jurnal Bina Praja

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Determinants of Paddy Field Conversion in 1995-2013

Wina Dwi Febrina * Research and Development Center National Land Agency Jl. H. Agus Salim No. 58, Menteng, Central Jakarta

Received: 25 November 2016; Accepted: 24 March 2017; Published online: 31 May 2017

DOI: 10.21787/jbp.09.2017.1-13

Abstract

side, economic growth needs more and more land for infrastructure growth. It was suggested that the growth would Java is the biggest rice supplier with the largest paddy field compared to other islands in . On the other

convert paddy field in Java to non-agriculture use. This paper reports the growth of land conversion, especially from paddy field to other utilization, in Java Island using panel data (provincial data 1995-2013). The data then treated as the dependent variable in the regression analysis for determining the factors that are significantly influential. The relative strengths of the influential factors are then compared using the concept of elasticity. It is found that farmers term of landtrade conversion. and GDP of manufacturing industries sectors significantly influence the land conversion. Meanwhile, the size of the population and the size of medium and large companies of manufacturing industries do not significantly influence the Keywords: Paddy Field Conversion, Determinant Factors

I. Introduction 2010). A land is a natural resource that is strategic A land is a resource that physically cannot be for development. Almost all sectors of the physical produced so that the supply of land is limited. On the development need land, such as agriculture, forestry, other side, the high demand for land for a variety of housing, industry, etc. activities tend to exceed the supply of available land. For agriculture, a land is a resource that is very important, both for farmers and for agricultural the scarcity of land leads to the competition of development. It is based on the fact that Indonesia This condition leads to scarcity of land. Furthermore, still relies on farming land (land-based agriculture consistent with Barlowe’s description in Butar- Butarland use (2012) and itthat can there cause is landcompetition conversion. in term This of is the quality of land resources can be improved, activities) (TB, Purwanto, F, & Ani, 2010). Although land use, because of the imbalance between limited but the quantity of land resource available in supply and unlimited demand. each region practically remained the same. On In these conditions, the increase in land the condition of these limitations, the increasing use requirements for an activity will reduce the need for land for housing, industry, infrastructure availability of land for other activities that can cause development, social services, and others will reduce the availability of land for agriculture. As a result, as a change of land use for an activity into other land conversion.use that is different Land conversion from previous can be activities. defined converted to non-agricultural use (Hidayat, 2008). a lot of agricultural lands, especially paddy field, is Land conversion is a phenomenon that cannot be avoided either in underdeveloped, developing, or Viewed from the economic side, the paddy field developed countries, in line with economic growth basedconversion on his can paddy be influenced production, by causing several nofactors incentive such as the farmer’s term of trade. The low term of trade and population growth (Azadi, Ho, & Hasfiati, * Corresponding Author © 2017 Library, Information, and Documentation Phone : +62 815 1365 2825 R&D Agency - MoHA all rights reserved. Email : [email protected] Accreditation Number 1 735/AU2/P2MI-LIPI/04/2016 for farmers to continue to live off their paddy Indonesia’s largest rice producer, so if the paddy fields in Indonesia (Isa, 2014). Considering Java is fields, so they tend to convert their farm. Besides have an impact on the food situation in the future. numberfarmers’ of term industries, of trade, particularly paddy field large conversion industry, Basedfield conversion on the exposure is not anticipated, above, the studyit is expected about the to inis which also thought the development to be influenced of an industry by the depends growing on the availability of land. Moreover, in the creation becomes important and relevant. of value added, the industrial sector also holds a determinant of paddy field conversion in Java development of industry, economic infrastructure, the increased role of the industrial sector in the GDP publicEconomic facilities, and growth settlements is characterized in which all require by the (Suriyanto,dominant position. 2012). This can be illustrated through land and increased demand for land to meet the needs of the non-agricultural. However, there is no agricultural land cannot be separated from the doubt that economic growth is also improving the Government’sThe rise ofattention. land conversion Various efforts that occursmade onby socio-economic condition in a non-agricultural land. the Government to ensure food security include the protection of agricultural land. One of the Efforts agricultural land that continues to increase along made by the government to protect agricultural withThese the conditions growth and are causedeconomic by development, the conversion that of land is through a juridical approach by issuing could not be avoided (Sudaryanto, 2004). policies. However, a research conducted by Irawan, Based on a research conducted by Pakpahan et. al. (2000) found that the regulations to protect (1993), at the regional level, the conversion agricultural land are still ineffective enough to control the conversion of agricultural land into Changes in the structure of the economy, population of paddy fields has been indirectly affected by isother precisely uses. Theretriggered is also by anthe indication mechanism that of paddy the growth, urbanization Flow, and consistency on the fields conversion, particularly in irrigated land, theimplementation construction of of transportation the spatial plan. facilities, Paddy land fields for industrialconversion growth, is also directlygrowth influencedin residential by Growth facilities, in Provincial/District Spatial Plan/RTRW (Isa, 2006). themThe can occurrencelower rice of production paddy field capacity, conversion while is research conducted by Ilham, Syaukat, & Friyatno aboutnot beneficial 95% of national for the agriculturalrice production sector results as one from of (2005),and distribution it shows ofthat paddy land fields.conversion According factors to theare grouped into three items, namely: economic factors, social factors, and existing land regulations. In terms conversionPaddy field in(Irawan, Indonesia, Purwoto, of course, Dabukke, are inseparable & Trijono, of the economy in Indonesia, In the micro level, the from2012). the Problems role of Java associated as a center with of therice paddy production. fields Java’s role in national rice production is quite large conversion, but at the macro level, the development although the extent is only 7% of the total land area ofdevelopment settlements, of proxied settlements by an affects increasing paddy number fields of Indonesia. Based on the distribution, Java has the of people, does not show a positive relationship. thousand hectares or 43% of the total area of paddy conversion is positively correlated with GDP growth largest paddy field, which is approximately 3,231 Meanwhile, based on the macro level, paddy field

Farmers Term of Trade

GDP of Manufacturing Industries

Paddy Fields Conversion

Numbers of Population

Regulation

Numbers of Medium and Large Scale Companies in Manufacture Industries

Figure 1. Mapping Framework of the Research

Jurnal Bina Praja 9 (1) (2017): 1-13 2 A. Quantitative Descriptive Analysis and paddy field conversion is negatively correlated with the farmers’ term of trade. Therefore, this The quantitative descriptive analysis is a thestudy farmers’ tries to term determine of trade the variable, factors thatan industrialinfluence performedmethod to using describe a mathematical paddy fields formula conversion as follows: that developmentthe occurrence seen of paddy from fieldsthe GDP conversion of the industrial based on occurred on the island of Java. The analysis is sector and the number of medium and large -At)=Lt-Lt-1 companies in the manufacturing industry and also the population variable. (∁t

Paddy fields conversion is defined as net paddy conversionTo review in Java? it, this Second, research what isis proposingthe determinant three fields conversion. This means that paddy fields area main questions. First, how is the growth of paddy field in year t (Lt) is the paddy fields area of the previous And third, how far is the regulations applied in order year (Lt-1) plus the new paddy fields (Ct) and the factors influencing paddy fields conversion in Java? occursreduced more paddy comprehensive, fields (At). Thus, respectively if the paddy in fieldsyear conversion is positive, it means a new paddy field ofto thiscontrol study paddy can befields illustrated conversion. as in Figure 1. ResearchSummarizing hypothesis the above can review, be thedescribed framework as t. Conversely, if the paddy fields conversion is etnegative, al., 2005). meaning that paddy fields reduced wider in Java is increasing. Second, the farmers’ term of than new paddy fields, respectively in year t (Ilham trade,follows: the first, GDP presumed of manufacturing that paddy industries, fields conversion numbers B. Statistical Analysis of the population, and numbers of medium and In accordance with the objectives and large scale companies in manufacturing industries hypothesis of the research, the relationship between conversion in Java. with significant influence towards paddy fields linear regression models (Juanda & Junaidi, 2012). variables can be described specifically in multiple This is based on previous research about the reliance is the dependent variable by one or more which is the research conducted by Kustiawan (1997) This analysis can be used to describe the extent of factors that affect paddy field conversion, one of independent variables. Based on the variables that described the multiple linear regression models, it was formulated as follows: regionalwhich stated development, that the external population factors growth that influenceand GDP the occurrence of paddy fields conversion are the Y=a+b X +b X +b3 X +b X +e the higher the rate of population growth and the 1 1it 2 2it 3it 4 4it t greatergrowth. theThe rate greater of GDP the growth rate regional resulted development, in extensive Information: increases of paddy field conversion. growth to provincial -i, the time period II. Method Y = -tThe (%) rate of paddy fields conversion

X1 growth to provincial -i, the time period GrossThe Domestic data used Product in this study(GDP) is insecondary manufacture data. = -tThe (%) rate of farmers term of trade The data consists of data on the size of paddy fields, X2 of population, and numbers of medium and large industries growth to provincial -i, the scaleindustries, companies farmers in termmanufacturing of trade (NTP), industries numbers in 5 = timeThe period rate -t of (%) GDP manufacturing provincial regions in Java, namely , central X3 Java, Yogyakarta, East Java, and Banten with time provincial -i, the time period -t (%) = The rate of population growth X4 of companies in the manufacturing theperiod form 1995-2013. of statistical The data data from is collected the published by learning, data, = industryThe rate ofgrowth medium provincial and large -i, thenumber time studying, and analyzing the source of literature in period -t (%) research. a = Constanta books, and scientific journals that are relevant to the b1, b2, b3

eit = error factors analyticalThe collected method dataused then is quantitative processed and descriptive analyzed = regression coefficient analysisin order toand answer statistical the problemsanalysis inusing research. multiple The with the time period of 1995-2013. Based on the variables through F test and partial correlation. the variationsThe data usedin the in formed the analysis assumptions, is panel there data linear regression methods to test the significance of are three approaches to the calculation of panel

Determinants of Paddy Field Conversion in Java 1995-2013 Wina Dwi Febrina 3 Table 1. Growth of Paddy Fields Conversion by Province in Java of 1995-2013 (Ha)

Central Year West Java Yogyakarta East Java Banten Java Java

1995-1997 Total -23.055 4.625 -1.080 -7.260 0 -26.770 conversion -7.685 1.542 -360 -2.420 0 -8.923 Average

1998-2000 Total -195.526 -1.249 -1.184 -5.388 -385 -203.732 conversion -65.175 -416 -395 -1.796 -128 -67.911 Average

2001-2003 Total -1.156 -2.939 -1.626 -49.763 -13.173 -68.657 conversion -385 -980 -542 -16.588 -4.391 -22.886 Average

2004-2006 Total 2.508 -33.255 -1.442 -11.756 -219 -44.164 conversion 836 -11.085 -481 -3.919 -73 -14.721 Average

2007-2009 Total -4.577 -471 -17 10.671 374 5.980 conversion -1.526 -157 -6 3.557 125 1.993 Average

2010-2013 Total -5.987 -14.671 127 -13.870 1.932 -32.469 conversion -1.497 -3.668 32 -3.468 483 -8.117 Average

1995-2013 Total -227.793 -47.960 -5.222 -77.366 -11.471 -369.812 conversion -11.989 -2.524 -275 -4.072 -604 -19.464 Average

Source: Statistics Indonesia (BPS), 1995-2013 (processed) data regression model (Firdaus, 2011), namely: occurs in all provinces in Java with a total conversion of about 370 thousand hectares, or approximately Method or PLS), (2) Fixed Effect Method (FEM), and (3)(1) Random Common-Constant Effect method Method (REM). (TheFurthermore, Pooled OLSthis 19 thousand hectares annually. This trend indicates Eviews 7.0 for estimating the determinant factors of that paddy fields conversion is greater than the new equation models are analyzed using the program industrialpaddy fields. or Thisservice conversion industries includes and conversion conversion toof paddy field into non-agricultural activities such as paddy fields conversion on Java in 1995-2013. as farm or plantation and horticulture. III. Results and Discussion agricultural activities other than paddy fields such conversion occurred during the year 1998-2000 A. The Growth of Paddy Fields Conversion Based on Table 1, the highest paddy fields in Java thousand hectares or approximately 68 thousand with total paddy fields converted about 204

The growth of paddy fields conversion in this sharplyhectares compared annually. Thisto the shows previous that periodin the periodin which of study is analyzed by looking at the changes in paddy economic crisis, paddy fields conversion increased fields area in each Java province. The growth of paddy fields conversion in Java in 1995-2013 can be hectares.the paddy Compared fields conversion to the inprevious 1995-1997, period, during the seen in Table 1. Based on Table 1, it can be seen that this period paddy field converted about 27 thousand during the year 1995-2013, paddy fields conversion Jurnal Bina Praja 9 (1) (2017): 1-13 4 economic crisis led to unemployment rising and Table 2. thepaddy subsequent field conversion cause a is decrease increased in about public 7.6%. revenue. The Paddy Field Conversion Rate by Province in Java, the year of 1995-2013 Most people who only have assets in the form of This situation triggered the paddy fields conversion. Paddy Field those who earn high incomes. Conversion Rate Province paddyAlong fields with will thesell theincreasing land to ofmaintain economic living level to at the average net per year (%) reduced, it can be seen throughout the year 2001- West Java 1.07 post economic crisis, the paddy field conversion is is 69 thousand hectares reduced about 44 thousand 0.26 hectares2003 which from the the amount year 2004-2006.of paddy field In conversionthe period Yogyakarta 0.47 be positive, meaning that the number of new paddy East Java 0.36 2007-2009 the overall paddy fields conversion even Banten 0.29 However,fields is higher unfortunately, than the reducedthis condition paddy fields.does Thenot new paddy field occurs about 6 thousand hectares. Java 0.57 again in 2010-2013 and reduced about 32 thousand last long, the paddy fields conversion in Java occurs Source: Statistics Indonesia (BPS), 1995-2013 (processed) stillhectares cannot paddy be controlled. field or about 8 thousand hectares annually. It indicates that the paddy field conversion

Based on paddy field conversion that occurs 0.47% per year. Third and fourth highest paddy in all province in Java, paddy field conversion in field conversion rate in Java is occupied by East Java West Java province is higher compared to other conversionprovince with rate net of about paddy 0.29% fields per conversion year, while rate the of aboutprovinces. 228 thousand Throughout hectares the Years or about 1995-2013 12 thousand West about 0.36% per year and Banten with paddy fields Java Province experienced paddy field Conversion province which experienced the sharpest increase last position with lowest paddy field conversion hectares per year. West Java province is also the Table 3. period that is about 195 thousand hectares or Paddy Field Conversion Rate by /City in Java, of paddy field conversion on economic crisis Year 2009-2013 conversion in the previous years. East Java is in the secondincreased position about 8.5%which from experienced the size ofhigher paddy paddy field Paddy Field Regency/City Conversion Rate conversion at central Java is about 77 hectares. at the Average Net/Year fields conversion. During 1995-2013, paddy field City -17.66

That was followed by Central Java at 48 thousand City -11.76 abouthectares. 11,5 Paddy thousand field conversionhectares, and in Bantenfollowed Province by DIY ofis inabout the fourth5 thousand position hectares. that the paddy field reduces City -8.76 City -6.17 conversionThe growth rate indicates of paddy the field percentage conversion of ispaddy also Tegal City -5.88 seen by a paddy field conversion rate. Paddy field Kudus City -5.86 field conversion speed that occurs in each province Cirebon City -5.53 2.in Java. The rate of paddy field conversion by provinces in Java in 1995-2013 can be seen in Table City -4.68

Based on Table 2, it can be seen that the net Surabaya City -4.31 Javarate Province of paddy experienced fields conversion the highest in Java rate overof paddy the period 1995 to 2013 is about 0.57% per year. West Yogyakarta City -3.24 Java, in which the value is about 1.07% per year. Cilegon City -2.15 field conversion compared to other provinces in

Source: Statistics Indonesia (BPS), 2009-2013 (processed) The second position is experienced by Yogyakarta province with a paddy field conversion rate of about Determinants of Paddy Field Conversion in Java 1995-2013 Wina Dwi Febrina 5 Table 4.

The Estimation Results Using Pool Ordinary Least Square (PLS) Method Variable Coefficient Std. Error t-Statistic Prob.

C 0.144938 0.118115 1.227089 0.2230

X1 -0.052569 0.009699 -5.419808 0.0000

X2 0.012045 0.001854 6.497371 0.0000

X3 0.140073 0.087902 1.593506 0.1146

X4 0.007954 0.006096 1.304716 0.1953

R-squared 0.441905 F-statistic 17.81571 Adjusted R-squared 0.417101 Prob(F-statistic) 0.000000

Source: Statistics Indonesia (BPS), 1995-2013 (processed) rate throughout the years 1995-2013 is occupied by companies in the manufacturing industries. Central Java province at 0.26% per year. Determination of the independent variables is based on previous research, especially research in all cities/regencies in Java in the last 5 years conducted by Ilham et al (2005) about the Based on the growth of paddy field conversion conversion rate is the highest in urban areas, as conversion in Indonesia, where the independent (2009-2013), it shows that in general, Paddy field variabledevelopment used andin this the study factors is also that one affect of the paddy variables fields used in the study. Farmers’ term of trade as a proxy shown in Table 3. for the competitiveness of agricultural products, by UrbanBased area. on Table Depok 3, cityin the experienced period of 2009-2013,the highest especially rice; GDP of the industrial sector and the highest paddy field conversion rate is dominated the number of medium and large companies in the by Bandung city on the second position with manufacturing industry as a proxy for industrial paddy field conversion rate at 17.66%, followed development, as well as a population as a proxy for occupied by (8.76%), Ciamis residential needs. 11.76%. third, fourth and fifth position, respectively also shows that the region with the highest paddy from BPS between 1995 and 2013 from 5 Provinces regency (6.17%) and Tegal city (5.88%). Table 3 in JavaThese by using factors Eviews are 7.0. calculated based on data province, such as Depok city, Bandung city, Cirebon regency,field conversion Ciamis isregency, dominated Cirebon by areas city in and West Bogor Java 3) Regression Analysis

the results of the estimation Pool Ordinary Least city (4.68%). The region that experienced highest SquareThe (PLS) model method, equations Fixed are Effects obtained Model based (FEM) on paddy field conversion rate in Central Java province Method and Random Effects Model (REM) Method is Tegal city and Kudus regency (5.86%). The region respectively as follows: conversionexperienced rate highest in 4.31%. paddy fieldYogyakarta conversion is a rateregion in East Java province is Surabaya city with paddy field a) Pool Ordinary Least Square (PLS) Method which suffered the highest paddy field conversion based on the results of the estimation provinceRate in Yogyakartais occupied by province the city isof Cilegon at 3.24%, by 2.15%. While Pool OrdinaryThe model Least equations Square method are obtained (PLS) the highest paddy field conversion rate in Banten is as follows: B. Determinant Factors of Paddy Fields

Conversion in Jawa Y=0.145-0.0526X1+0.012X2+0.140X3+0.008X4 basedThe on determinantthe effect of factorsthe farmers’ that influence term of paddytrade, Ordinary Least Square (PLS) Method in GDPfields of conversion manufacturing in Java industriesin this study sector, were numbersanalyzed The estimation results using Pool of population and number of medium and large errors, t-statistics and analysis results are the form of value coefficients, standard

Jurnal Bina Praja 9 (1) (2017): 1-13 6 Table 5.

The Estimation Results Using Fixed Effect Models (FEM) Method Variable Coefficient Std. Error t-Statistic Prob.

C 0.218752 0.141169 1.549577 0.1249

X1 -0.053836 0.009472 -5.683664 0.0000

X2 0.011915 0.001801 6.615373 0.0000

X3 0.119965 0.089746 1.336719 0.1848

X4 0.007233 0.006050 1.195664 0.2351

Cross-section fixed (dummy variables)

R-squared 0.458628 F-statistic 9.106971 Adjusted R-squared 0.408268 Prob(F-statistic) 0.000000

Source: Statistics Indonesia (BPS), 1995-2013 (processed)

the intercept every region is different, depending on the value of the dummy b) Fixedpresented Effect in Model Table (FEM) 4. Method errors, t-statistics and analysis results are based on the results of the estimation (Di). The coefficient of basic, standard usingThe Fixed model Effect equations Model are(FEM) obtained is as follows: c) Randompresented Effect in Table Model 5. (REM) Method

based on the results of the estimation Y=0219+D-0.0543X1+0.0119X2+0.120X3+0.007X4 usingThe Random model Effect equations Model are(REM) obtained is as In equations using FEM method, the follows: slope for farmers term of trade, the GDP of

manufacturing industries sector, numbers Y=0219-0.065X1+0.0117X2+0.135X3+0.002X4 of population and the number of medium and large companies in the processing In the equation using the method industries applicable to all regions i, but of this method, error component of each

Table 6.

The Estimation Results Using Random Effect Models (REM) Method Variable Coefficient Std. Error t-Statistic Prob.

C 0.219056 0.316720 0.691640 0.4909

X1 -0.064911 0.028506 -2.277106 0.0251

X2 0.011670 0.005088 2.293663 0.0241

X3 0.134603 0.180525 0.745623 0.4578

X4 0.001712 0.017463 0.098011 0.9221

R-squared 0.099697 F-statistic 2.491596 Adjusted R-squared 0.059684 Prob(F-statistic) 0.048615

Source: Statistics Indonesia (BPS), 1995-2013 (processed)

Determinants of Paddy Field Conversion in Java 1995-2013 Wina Dwi Febrina 7 Table 7.

The Estimation Result of Likelihood Test Ratio Between FEM and PLS Method Effects Test Statistic d.f. Prob.

Cross-section F 0.229591 (4.86) 0.9211

Source: Statistics Indonesia (BPS), 1995-2013 (processed)

Y=0.145-0.053X1+0.012X2+0.140X3+0.008X4 basic, standard errors and t-statistics and region is different. The coefficient of 1. C constant value of 0.145 means that if Basedanalysis on several results methods are presented above, inthen Table some 6. theThe equationfarmers’ showsterm ofthat: trade, the number of tests are used to choose which method is the most population, and the number of medium and large companies in the manufacturing used to chose which one is more appropriate for appropriate. Chow Test or Likelihood Ratio Test is will grow to 0.145%. 2. b(X1)industries = -0.053 is 0, meansthen the that paddy if the fields farmers’ conversion term of PLS and FEM methods. The estimation results of trade is increased by 1%, while other variables theChow probability Test or Likelihood for the RatioCross-section Test using F Eviewsis 0,9211, 7.0 whichcan be isseen over in 0.05 Table (Decision: 7. The test accept results Ho), showed Ho, in thatthis will be decreased by 0.053%. Sign (-) indicates case, indicates that the PLS method is better than aremained, negative then correlation the paddy between fields conversion the inverse (Y) FEM method, so it can be concluded that in 95% or opposite of the farmers’ term of trade and method. confidence level, PLS method is better than the FEM conversionpaddy fields will conversion, be low. that is, if the farmers’ method between FEM and REM method. Based on 3. b(X2)term of= 0.012 trade means is high, that then if the the variable paddy fieldGDP Hausman test is used to find the appropriate of manufacturing industries sector increased the probability value for the Cross-section F is over by 1%, while other variables remained, the 0.05,the result which of indicates Hausman the test condition in Table accepts 8, it shows Ho. that In this case, Ho is indicating the REM is better by 0.012%. Sign (+) positive indicates the than FEM method. So that as the value of probability samepaddy direction fields conversion of the relationship (Y) will bebetween increased the for the Cross-section F is 0,7055, it can be concluded GDP of manufacturing industries sector and than FEM method. of manufacturing industries sector is high then that inBased 95% onconfidence the result level, of REMa series method of estimates is better conversion of paddy fields, that is, if the GDP above, it can be seen that the model equations 4. b(X3) = 0.140 means that if a variable number generated by the PLS method is better in explaining ofthe population paddy field increasedconversion by will 1%, also while be high. other number of population and the number of medium (Y) will increase by 0.140%. Sign (+) positive andthe influencelarge companies of variable in farmers’ the termmanufacturing of trade, indicatesvariables remained,the same the paddydirection fields relationship conversion between the number of population and the Based on estimates by PLS method, obtained the followingindustries equation: of the vast paddy fields research areas. willpaddy also fields be high. conversion that is, if the number of population is high, the paddy fields conversion

Table 8.

The Estimation Result of Hausman Test Between FEM and REM Method Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.

Cross-section random 2.164429 4 0.7055

Source: Statistics Indonesia (BPS), 1995-2013 (processed)

Jurnal Bina Praja 9 (1) (2017): 1-13 8 5. b(X4) = 0.008 means that if a variable number variable farmer’s term of trade and of medium and large companies in the the number of medium and large manufacturing industry is increased by 1%, companies in the manufacturing industries of -0.016026. this means conversion (Y) will be increased by 0.008%. not happen Multicollinearity signwhile (+) other positive variables indicates remained, the thesame paddy direction fields between the farmer’s term of relationship between the number of medium trade variable and number of and large companies in the manufacturing medium and large companies in the manufacturing industries because if the number of medium and large companies the magnitude of the correlation inindustries the manufacturing and paddy fields industries conversion, is high that then is, 0.8 then we can say “pass the Multicollinearitycoefficient is -0.016026 test “. less than 4) Classicalpaddy fields Assumption conversion Test is also high. • variables GDP of manufacturing model assumption, it must meet the Classic industriesThe correlation sector and coefficients a number forof assumptionTo be accepted test, which as includes:a multiple linear regression the population are -0.548850. this means not happen Multicollinearity a) Normality Test between GDP of manufacturing Based on the test results of normality industries sector variables and a treated with 7.0 eviews program, it number of population. because can be obtained that the shape of the the magnitude of the correlation histogram is distributed asymmetrically so that we expected residuals to be 0.8, then we can say “pass the normally distributed. Based on statistical Multicollinearitycoefficient is -0.548850 test “. less than test Jargue bera statistical value of • 1.528706 with 46.56% probability, it GDP of manufacturing industries can be concluded that the residuals sectorThe correlationvariables and coefficients the number for were normally distributed and pass the of medium and large companies test for normality so that testing data is in the manufacturing industries appropriate to proceed in the study. are -0.005481. this means Multicollinearity does not happen b) Multicollinearity Test between GDP of manufacturing From the data processing through the industries sector variable and eviews 7.0 program, it can be concluded: a number of medium and large • companies in the manufacturing variable farmer term of trade and industries because of the magnitude theThe GDP correlation of manufacturing coefficient industries for the sector amounted to -0.210224. -0.005481 less than 0.8 then we can sayof “pass the correlationthe Multicollinearity coefficient test “. is does not happen between variable • rateThis and means the thatGDP Multicollinearity manufacturing number of population variables and The correlation coefficients for the industries because of the correlation the number of medium and large companies in the manufacturing can say “pass the Multicollinearity industries are -0.045813. this testcoefficient “. is less than 0.8. Then we means not happen Multicollinearity • between a number of population the variable of farmers’ term variables and the number of ofThe trade correlation and the coefficient number forof medium and large companies in the manufacturing industries because Multicollinearity does not happen the magnitude of the correlation betweenpopulation the at term0.121284. of trade This variable means and a population of farmers because 0.8 then we can say “pass the coefficient is l-0.045813 ess than the magnitude of the correlation Multicollinearity test “.

0.8, it can be said to “pass the c) Heteroskedasticity Test Multicollinearitycoefficient is 0.121284 test “. less than Based on heteroscedasticity test •

The correlation coefficient for the through eviews 7.0 program, we can find Determinants of Paddy Field Conversion in Java 1995-2013 Wina Dwi Febrina 9 that the probability value Obs * R-squared concluded that a variable number of are 0.2769. Because the probability value Obs * R-squared are 0.2769 > 0.05, there is no heteroscedasticity. Java.the population did not significantly • influence paddy fields conversion in d) Test Autocorrelation companies in the manufacturing Based on Autocorrelation test industriesThe number Variable of medium and large Based on the estimation by eviews that the probability value Obs * R-squared 7.0 program for a number of arethrough 0.5006. eviews Because 7.0 program, the probability we can value find medium and large companies in the Obs * R-squared are 0.5006 > 0.05 can manufacturing industries Variable, be concluded that in this research model the result obtained the probability passes autocorrelation test. because of the probability value is e) Test of linearity value (significance) = 0.1953. Thus Based on the linearity test through can be concluded that the number of eviews 7.0 program, we know the value mediumless than and 0.05 large α (0.1953 companies < 0.05), in the it manufacturing industries Variable probability of 0.6352 > 0.05 so that we canof the conclude F probability this research of 0.6352. model Thus, linearity the test passes. did not significantly influence paddy b) F Testfields conversion in Java. 5) Hypothesis Testing Based on the estimation by eviews 7.0 program, probability value obtained a) t-Test for the F-statistic is equal to 0.000000. • Farmers’ term of trade variable Based on the estimation by eviews Thus because of the probability value 7.0 program for farmers’ term of (0.000000 > 0.05). It can be concluded (significance) is greater than α 0.05 trade variable, the result obtained that simultaneously, the farmers’ term of trade, the GDP of manufacturing industries sector, the number of population, and the probability value (significance) number of medium and large companies (0.0000= 0.0000. < 0.05). Thus It can because be concluded of the in the manufacturing industries variables thatprobability the farmers’ value less term than of α trade 0.05 conversion in Java. significantly influence the paddy fields • variable significantly influences the 6) Coefficient of Determination sectorpaddy Variablefields conversion in Java. Based on the estimation through the program BasedThe GDP on of the manufacturing estimation byindustries eviews

manufacturing industries sector resulteviews for 7.0, adjusted the coefficient R-Squared of value determination is 0.417101. can Variable,7.0 program the forresult The obtained GDP of be seen from the adjusted R-Squared value. The

numberThis means of population that 41.71% and of paddythe number fields ofconversion medium probability value (significance) andin Java large is companiesinfluenced inby the farmers’ manufacturing term of industriestrade, the (0.0000= 0.0000. < 0.05), Thus it can because be concluded of the thatprobability the valueGDP is lessmanufacturing than α 0.05 by other variables which are not examined in this study.variables, while the remaining 58.29% is influenced Based on the results of the analysis inindustries Java. variables significantly determined by using the PLS (Pool Ordinary Least • influence the paddy fields conversion Square) method, it can be seen that together Based on the estimation by eviews (simultaneously) the farmers’ term of trade, the 7.0The numbersprogram offor population the number Variable of GDP of manufacturing industries sector, the number population variable, the result of population, and the number of medium and large obtained probability value companies in the manufacturing industries variables

because of the probability value less Java. From the F test results, it can be seen that the (significance) = 0.1146. Thus probabilitysignificantly value influence for the paddy adjusted fields R-squared conversion value in

than 0.05 α (0.1146 < 0.05), it can be Jurnal Bina Praja 9 (1) (2017): 1-13 10 (E). Elasticity criteria are as follows: trade,of 0.417101 the number indicates of population, that 41.41% and of the paddy number fields of • E > 1 = elastic mediumconversion and in large Java iscompanies influenced in by the farmers’ manufacturing term of • E < 1 = inelastic industries variables, while the remaining 58.29% is • E = 1 = uniter • E = 0 = perfectly inelastic study. • E = ~ = perfectly elastic influenced by other variables not examined in this

Based on the research, we find that the seen in the estimated equation below: farmers’ term of trade significantly influence the As for the influence of these variables, it can be paddy field conversion in Java is in accordance with trade caused no incentive for farmers to continue to Y=0.145-0.053X1+0.012X2+0.140X3+0.008X4 the initial hypothesis of the study. The low term of From the equation, we can conclude the live in their paddy field production, so they tend to the GDP of manufacturing industries sector variable elasticity of each variable. Based on a slope, the convert their paddy fields (Ashari, 2003). Similarly, value of Farmers’ term of trade variable amounted to -0.053, it can be seen that the elasticity value significantly influenced paddy fields conversion, it role of the industrial sector in the GDP stimulated of Farmers’ term of trade variable towards paddy governmentindicates that prioritiesindustrial activitiesto shift andfrom the agriculture size of the to the industrial sector. For farmers, the increase value of GDP of manufacturing industries sector in industrial sector becomes one of the factors variablefields conversion amounts isto -0.053.0.012, it Based can be on seen a slope, that the to switch professions to become workers in the elasticity value of GDP of manufacturing industries industrial sector and convert their land into other 0.012. Based on the estimation by eviews 7.0 program sectorBased variable on elasticity towards valuepaddy of fields the farmers’conversion term is uses rather than the paddy field. for the number of population variable, the result of trade variable and the GDP of manufacturing industries sector variable which is smaller than 1, it is indicated that the farmer’s term of trade obtained probability value (significance) = 0.1146. variable and the GDP of manufacturing industries Thus because of the probability value is less than 0.05 α (0.1146 < 0.05), the number of population conversion. Based on the estimation by eviews conversion. It showed that every 1% increase in the 7.0variable program did notfor significantlythe medium influenceand large paddycompanies field sector variable are inelastic towards paddy fields in the manufacturing industry variable, the result conversion amounted to 0.053%. Instead, each 1% increasefarmers’ termin the of GDP trade of willmanufacturing decrease paddy industries fields obtained probability value (significance) = 0.1953. amounted to 0.012%. theThus, number because of themedium probability and large value companies is less than in sector will improve paddy fields conversion the0.05 manufacturing α (0.1953 < 0.05), industries It can bevariable concluded did thatnot C. Government Regulations to Control Paddy Fields Conversion correspondsignificantly to influence the initial paddy hypothesis fields of conversion the studies. in Java. This result shows that both variables did not Paddy field is a private good that is legal to such as on farmers’ term of trade variable pointed be transacted. Therefore, the efforts to limit the out thatThe the negative increase slope of farmers’ of the variables term of trade equation will fromoccurrence the factors of paddy that cause field conversionthe occurrence can of be paddy done is merely control. The control should be the start contrast, the positive slope such as on the GDP of manufacturingcause the decrease industries of the sectorpaddy pointedfield conversion. out that the In legal instruments (Ilham et al., 2005). One of the fields conversion, there are economic, social, and increase in GDP of manufacturing industries sector efforts made by the government to control the

One of the interesting properties in empirical approach by issuing various regulations such as caused the increase in paddy field conversions. Lawconversion of the Republic of paddy of fieldsIndonesia is through Number a 5 juridicalof 1960 measure the elasticity of Y with respect to X, or on the Basic Regulation of Agrarian Principles, Law inresearch other words, model the is thatpercentage the slope change coefficient in Y for (β) a of the Republic of Indonesia Number 12 of 1992 given percentage change in X (Gujarati, 2007). In concerning Plant Cultivation System, Law of the Republic of Indonesia Number 26 of 2007 on Spatial Planning, Law of the Republic of Indonesia Number symbolic, if ΔY indicated the changes of paddy field 41 of 2009 on Sustainable Land Farming Protection, conversion (Y) and ΔX indicated the changes in a as well as the Presidential Regulation and other variable that influence paddy field conversion (X), then it can be defined as a coefficient of elasticity Determinants of Paddy Field Conversion in Java 1995-2013 Wina Dwi Febrina 11 government regulation. However, the actual fact showed that the stated in RTRW 2007, which is consist of the area for technical irrigated paddy fields amounted to 58.680 control of paddy fields conversion through juridical Ha and rainfed paddy fields area amounted to 2.486 (2008)approach states is not maximizedthat the biggest in overcoming obstacle problems in the Ha. This means that there is an actual technical protectionof paddy fieldsof agricultural conversion. land is Lichtenberg institutional & aspect Ding irrigated paddy field amounted to 18.400 Ha that rather than on the physical aspects. Failure to set the is not included in the allocation of paddy fields institutional aspects affect the demand and supply of designation on RTRW 2007 so that it can stimulate land to be converted. A juridical instrument that has the occurrencespatial instrument of paddy thatfields expected conversion to inprovide those been developed by the government have not applied areas. Thus, based on the case above, it turns clear sanctions, overlapping and not supported by economic and social instruments (Irawan, 2008). protection for paddy fields precisely triggering the occurrence of greater paddy fields conversion. IV. Conclusion Based on the estimation result it can be technicalThis causes irrigation the paddy potential fields forconversion rice production. rate is still quiteFor large example, even venturing the implementation into paddy fieldsof Law with of conversion occurs at all provinces in Java with total the Republic of Indonesia Number 41 of 2009 is conversionseen that during about 370.000 the year Ha, 1995-2013 or about paddy19.000 fieldHa/ plagued with the overlapping rules of other laws, year, with conversion rate are about 0.57% annually. such as Law of the Republic of Indonesia Number 23 of 2014 on Regional Government, where the Regional Government has authority to assign 2013West Javawith Provincetotal conversion experienced about the 228.000 largest Ha, paddy or a function area. Agriculture is only a matter of aboutfield conversion 12.000 Ha/year. in Java throughout the years 1995- choice for Regency/City Government in the Law Based on the resulting equation models, can of the Republic of Indonesia Number 23 of 2014. be seen that the farmers’ term of trade variable and local agricultural sector. Irawan (2008) states that regionalThese conditions Government increase focus theon the chances progress of ignoring of their onGDP the of slopemanufacturing and the elasticity, industries in sectorpartial, significantly it is known region that viewed from the economic growth and thatinfluences each 1% the increase paddy fields in the conversion farmers’ interm Java. of Based trade to increase investment in the non-agricultural sector to 0.069%. Instead, each 1% increase in the GDP of asrevenue it can (PAD), generate The Regionalgreater revenueGovernment and are promote trying thewill manufacturingbe lowered paddy industries fields conversion will improve amounted paddy faster economic growth. Consequently, if the case demands conversion of agricultural land to be used slope value of less than 1 indicates that the farmers’ for other nonagricultural uses, the local government termfield conversionof trade variable amounted and GDP to 0.287%, of manufacturing where the is less likely to consider a ban on land conversion applicable. conversion. Furthermore, inconsistency between industries sector are inelastic towards paddy fields to be controlled considering the vast reduction of Moreover, paddy fields conversion in Java needs instrumentpaddy fields can conversion also trigger controlthe occurrence objectives of paddy and determining the extent of paddy fields in the spatial paddy fields area in Java. Efforts to control paddy conducted by Dewi (2010) which showed that fields conversion in Java can be done by reducing fields conversion. This can be seen in the research the factors that affect paddy fields conversion. The effort required in order to reduce the paddy fields the Spatial Plan/RTRW as an instrument layout is conversion in Java is to fix the farmers term of trade, precisely triggered by the occurrence of paddy fields in industries developments in order not to convert a especially paddy fields farmers and do monitoring conversion. This occurs due to the incompatibility of determining the extent of paddy fields contained in policy of increasing the purchasing power of farmers paddy fields for the industrial expansion, that is the the RTRW with the actual area where it turns paddy so that farmers term of trade increased. Besides fields area listed in the RTRW are smaller than the that, it also needs policies in land conversion control actual paddy fields. For example, The Study which due to the development of industrial activities such comparing two RTRW in Regency year 1999 as monitoring the granting of land use, especially and 2007 showed that in the RTRW 1999, vast areas allocated for paddy fields is 66.937 hectares, while However, currently, the regulations to protect paddy fields for other uses. in RTRW 2007, the area designed for paddy fields agricultural land still have not effective enough to throughdecreased spatial into 51.093 analysis, Ha. it This is known means thatthat therebased has on been a decline in the paddy fields area. In addition, another use. Overlapping rules, rules that have not supportedovercome problemsby economic of paddy and fields social conversion instruments, into the facts, the actual paddy fields area is larger than Jurnal Bina Praja 9 (1) (2017): 1-13 12 and have not applied clear sanctions, and also Kebijakan Konversi Lahan. FORUM control objectives and determining the extent of Retrieved from http://pse.litbang.pertanian. inconsistency between paddy fields conversion go.id/ind/index.php/publikasi/forum-agro-PENELITIAN AGRO EKONOMI, 26(2), 116–131. ekonomi/312-forum-agro-ekonomi-vol26- inpaddy Java fieldsand in infact, the precisely spatial instrumenttrigger the occurrence still being obstacle in order to control paddy fields conversion kebijakan-konversi-lahan Irawan,no02-2008/2084-meningkatkan-efektifitas- B., Purwoto, A., Dabukke, F. B. M., & of greater paddy fields conversion. Acknowledgement Pertumbuhan Produksi Padi di Luar Pulau Jawa.Trijono, RetrievedD. (2012). Studifrom Kebijakanhttp://pse.litbang. Akselerasi and guidance in giving me full strength to complete pertanian.go.id/ind/index.php/laporan- this Paper.First of A all,lot praiseof thanks to Allah, to my SWT tutors for Prof. his mercy Dr. Ir. hasil-penelitian/2530-laporan-hasil- penelitian-2012 from Bogor Agricultural University (IPB), for their Isa, I. (2006). Strategi Pengendalian Alih Fungsi support,DS Priyarsono research and assistant Prof. Dr. and Ir. Noervaluable Azam comments Achsani Lahan Pertanian. In A. Dariah, N. L. Nurida, to revise the Paper. Great appreciation to the Irawan, E. Husen, & F. Agus (Eds.), Prosiding Research and Development Centre of Ministry Seminar Multifungsi dan Revitalisasi Pertanian of Agrarian and Spatial Planning for giving me (pp. 1–16). Jakarta: Indonesian Agency for permission and supports during conducting the Agricultural Research & Development, Ministry paper. Also Special thanks to my families for the of Agriculture; Ministry of Agriculture, Forestry extraordinary supports. and Fisheries, Japan; ASEAN Secretariat. Retrieved from http://balittanah.litbang. V. References pertanian.go.id/ind/index.php/en/publikasi- mainmenu-78/27-prosiding3 land conversion drivers: A comparison between Isa, I. (2014). Alih Fungsi Lahan dan Ketahanan Azadi,less H., Ho,developed, P., & Hasfiati, developing L. (2010). and Agriculturaldeveloped countries. Land Degradation & Development, Juanda, B., & Junaidi. (2012). Ekonometrika Deret 22(6), 596–604. http://doi.org/10.1002/ Pangan: Konflik Penggunaan Tanah. Jakarta. ldr.1037 Law of the Republic of Indonesia Number 12 of 1992 Butar-Butar, E. G. V. (2012). Analisis Faktor- concerningWaktu : Teori Plant dan Aplikasi.Cultivation Bogor: System, IPB Press.Pub. L. No. 12 (1992). Indonesia. di Provinsi Jawa Barat. Bogor Agricultural Law of the Republic of Indonesia Number 26 of 2007 University.faktor Konversi Retrieved Lahan from Sawah http://repository. Irigasi Teknis on Spatial Planning, Pub. L. No. 26 (2007). ipb.ac.id/handle/123456789/56144 Indonesia. Law of the Republic of Indonesia Number 41 of sebagai Instrumen Pengendali Perubahan 2009 on Sustainable Land Farming Protection, Dewi,Penggunaan I. A. (2010). Lahan Analisis Sawah Efektifitas menjadi Penggunaan Tata Ruang Pub. L. No. 41 (2009). Indonesia. Lahan Non Pertanian di Kabupaten Bekasi. Law of the Republic of Indonesia Number 5 of 1960 School of Business - Bogor Agricultural on the Basic Regulation of Agrarian Principles, University. Pub. L. No. 5 (1960). Indonesia. Firdaus, M. (2011). Aplikasi Ekonometrika untuk Lichtenberg, E., & Ding, C. (2008). Assessing farmland protection policy in China. Land Use Hidayat, S. I. (2008). Analisis Konversi Lahan Sawah Policy, 25(1), 59–68. http://doi.org/10.1016/j. Data Panel dan Time Series. Bogor: IPB Press. landusepol.2006.01.005 Retrieved from http://jurnal.unej.ac.id/index. Suriyanto, A. (2012). Analisis Beberapa Variabel php/JSEP/article/view/431di Propinsi Jawa Timur. J-SEP, 2(3), 48–58. yang Mempengaruhi Konversi Lahan Pertanian Ilham, N., Syaukat, Y., & Friyatno, S. (2005). di Kabupaten Sidoarjo. Universitas Negeri Perkembangan dan Faktor-faktor yang Surabaya. Mempengaruhi Konversi Lahan Sawah serta Dampak Ekonominya. SOCA (Socio-Economic Dampak Alih Fungsi Lahan Pertanian ke Sektor of Agriculture and Agribusiness), 5(2), 1–25. TB, C., Purwanto, J., F, R. U., & Ani, S. W. (2010). Retrieved from http://ojs.unud.ac.id/index. php/soca/article/view/4081 Non Pertanian Terhadap Ketersediaan Beras http://fp.uns.ac.id/jurnal/jurnal-88.htmldi Kabupaten Klaten Provinsi Jawa Tengah. Caraka Tani, XXV(1), 38–42. Retrieved from Irawan, B. (2008). Meningkatkan Efektifitas

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