AFFECTING FACTORS TRANS LAND FUNCTION IN BALI

Vol. 15 No.1, Februari 2022

ISSN : 2301-8968

EKONOMI

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TERAPAN

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The Effect of Banks and Cooperatives in Improving Welfare Inayati Nuraini Dwiputri, Lustina Fajar Prastiwi, Grisvia Agustin

ISSN 2301-8968

Denpasar

Februari 2022

Halaman

1-161

The Role of Social Capital with Local Wisdom in Household Food Security in Bali Province Putu Ayu Pramitha Purwanti, Ida Ayu Nyoman Saskara

Middle Income Trap In A Macroeconomic Perspective A Case Study In Indoensia Apip Supriadi

Trade-Environment Triangle in Indonesia: Ecological Footprint Approach Kuratul Aini, Djoni Hartono

Social And Financial Efficiency Of Lembaga Perkreditan Desa Kajeng Baskara

The The Relationship Between Fiscal Policy And Civil Liberty On Per Capita GDP In Indonesia During 1980-2018

Vita Kartika Sari, Malik Cahyadin

The Effect Of Fiscal Decentralization On Economic Growth: A Study Of The Province Level In Indonesia Setyo Tri Wahyudi, Lutfi Kurniawati

The United States’ Monetary Policy Spillover Effect Against Rupiah -Us Dollar Exchange During Usa – China Trade War

Andryan Setyadharma, Anisa Rahmawati, Anisa Rahmawati

Affecting FactorsTrans Land Function In Bali

I Wayan Sudemen, I Ketut Darma

The General Allocation Fund (DAU) Formulation Policy: Incentives or Disincentives to the Fiscal Independence of Local Governments Kun Haribowo, Latri Wihastuti

Impact Of Rural Development Program On Agriculture Production and Rural-Urban Migration In Indonesia Murjana Yasa, Wayan Sukadana, Luh Gede Meydianawathi

Volume 15    Nomor 1

pISSN : 2301 – 8968

JEKT ♦ 15 [1] : 91-126

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AFFECTING FACTORSTRANS LAND FUNCTION IN BALI

ABSTRACT

Agricultural land conversion is one of the phenomena of changing agricultural land become non-agricultural as a result of development carried out by the government, private and public that alone. Destination in study this is identify factors that influence land use change in Province Bali. This study uses a quantitative approach using analytical tools panel data regression which is a combination of time series or time series data and cross section data. The results showed that The occurrence of conversion of paddy fields in regencies/cities in Bali Province is influenced by by total population, GDP per Capita and share Agriculture to GRDP. It turns out development total population whose influence significant with level real 95% (α = 5%), moderate which other non-significant .

Keywords : Quantity Population, GDP per capita, Share Agriculture, Switch FunctionLand

ABSTRACT

Conversion of agricultural land is one of the phenomena of the change of agricultural land to non-agricultural as a result of development carried out by the government, self-sufficiency and the community itself. The aim of this study was to identify factors that affect land transfer in Bali Province. This research uses a quantitative approach using panel data regression analysis tools that are a combination of time series or time series data and latitude or cross section data. The

results showed that the transfer of rice field functions in districts / cities in Bali

Province was influenced by the number of residents, PDRB per Capita and

agricultural share to PDRB. It turns out that the development of the population whose influence is significant with a real level of 95% (α = 5%), while others are

non-significant.

Keywords: Population, PDRB Per capita, Share of Agriculture, Land Transfer

PENDAHULUAN

effects and negative effects, even though the

Development is something process change to direction which more good in environment public, with existence process change here will have an impact on changes

purpose from development that alone attempted avoid effect negative, because with process source power which limited. Enter era globalization necessary facilities

in the related sectors, because every time ^{and infrastructure to support the}

there is change will certainly bring positive ^{implementation of development, one of}

them is land. Land plays an important role as land for realize development in Thing this is development physical. Like known, soil no could separated with man because soil is one of the important factors in human life. Land is the place settlement, the place do activity man, even after even die still need land. Land which meant is soil.

In development of course will need source power, like for example land, because land is resource natural strategic for development. Almost all physical development requires land, in the field of In agriculture, land is a very important resource, both for farmers as well as for agricultural development. This is based on the fact that in Indonesia activity Agriculture still focus on land ( land based agriculture Are activities ). Rapid development recently implemented by government, very big the effect to sector Agriculture specifically Agriculture which irrigated (ricefield), sector Agriculture have role which very urgent in growth economy.

Because sector this many absorb workers, especially workers who do not have the skills or labor that is not absorbed in other sectors, because the agricultural sector does not need skill (skills) high. the size potency agriculture can seen from historical experience, it turns out that the monetary crisis and economic crisis in Indonesia can be handled by a group of small businesses, both in the field of processing industry and in field Agriculture (Suparmoko, 2002).

The agricultural sector is a strategic sector and plays an important role in economy national and continuity life public, especially in the contribution to GDP, provider field work, and provider food domestic. Rice fields have an important meaning, namely as a medium of activity farming in order to produce staple food (especially rice) for need people man. However with development era and dynamics motion step development as well as growth total population, existence land start disturbed. Wrong one problem which

enough related with existence plant Paddy is more and more widespread over function land Agriculture usage other like development settlement population, industry, shops, and tourism and that other.

The conversion of land functions, especially rice fields or often called as conversion land is change function part or whole area land from function beginning for example Agriculture irrigated (ricefield) Becomes function non Agriculture. Switch function land also could interpreted as changes for other uses are caused by factors that are linearly big covers necessity for fulfil need population which more increase amount and increase demands will quality life which more good. Switch function land usually related with process development territory, it can even be said that land conversion is a consequence from development region, like for example with development total population. Growth population which so fast, as well as intensity development which develop in various field of course just will lead to an increase in the demand for land. Where is the farm 93

productive will be used for housing construction, supporting facilities tourism such as hotels, villas , home stays , and others. This is what then push transfer occurs function land agriculture to non Agriculture or industry.

Growth wide area Becomes problem which very are you serious because compete with high population growth, industrialization and development infrastructure public. Thing this which has push happening conversion land Agriculture to non Agriculture. factors which determine land conversion is grouped into three, namely economic factors, social factors, and regulation which issued good by government area in skeleton regional autonomy, as well as by the central government, especially those related to land. The research of Syafa'at et al . (2001), in the main rice production centers in Java and outside Java, show that Besides factor technical and institutional, economic factors that determine the conversion of paddy fields to agriculture and non-agricultural agriculture, are (1) the competitive value of

rice against other commodities decreases; (2) response farmer to dynamics market, environment, and power farming competitivenessincrease.

Temporary study Sumaryanto, Hermanto, and Passport (in Witjaksono, 1996), in Java showed that the conversion of paddy fields to non- Agriculture (63 percent) more tall compared to to Agriculture non ricefield (37 percent). Of the 63 percent, 33 percent are for settlements, 6 percent are for industry, 11 percent for infrastructure and 13 percent for others. Apart from factors economic, social factors also affect land conversion. According to Witjaksono (1996), there is five factor social which influence over function land, that is change behavior, connection owner with land, solving land, decision-making, and the government's appreciation of the aspirations of the people. With fast development development which implemented by government and society bring impacts on land, in particular irrigated agricultural land

(rice fields). If this condition continues without there are efforts to save and protect productive agricultural land then productive agricultural lands will continue to be converted and increasingly reduced . As is known, Indonesia is an agricultural country, most of population Indonesia domiciled in area rural and have eye livelihood sector Agriculture. Until moment this, sector Agriculture is sector strategic and play a role important in economy national and continuity life public, especially in donation to GDP, provider field work, and provision food in country. Awareness to role the causing part big public still permanent maintain their agricultural activities. “Various data show that in some developing countries over 75 percent of the population is in the agricultural sector and more than 50 percent of national income is generated from sector Agriculture as well as almost whole the export is ingredient Agriculture" (Ario, 2010 in Adhi Yudha Bhaskara, et al).

Government policies regarding

agriculture are mostly not in favor of the agricultural sector itself. This can be seen with more a lot over function land Agriculture Becomes land non Agriculture. Land Agriculture Becomes victim for fulfil need will settlement and irresponsible industry. The conversion of agricultural land is consequence from consequence increase activity and total population as well as other development. Land conversion is essentially a matter of which is normal in the modern era like today, but land conversion on reality bring many problem because occur on land Agriculture which still productive. Land Agriculture could give many benefits in terms of economic, social, and environmental. However, if the function switch productive agricultural land is left alone and not controlled, of course will have a negative impact on the community itself, considering it is so important and useful agricultural land for the community itself.

Bali is wrong one province which there is in Indonesia which also experience over function land which enough dramatic. Almost all area touched and land 95

Agriculture productive switch function Thing this caused by rapid development, especially tourism development and the increasing level well-being people Bali, because development tourism That's why we need accommodation supporting Bali tourism. Land conversion in Bali is unavoidable in the midst of the huge demand for houses, facilities tourism, economic development and others. Good investors Domestic and foreign investors have penetrated to remote areas of Bali, elsewhere party Agriculture by natural still very needed for support the life and sustainability of the Balinese ecosystem. It seems not only applies to the past, but also to the present and the future come. As a sector of life, agriculture is almost said to be absolutely necessary by the whole of Balinese life and society, because agriculture is a one of the components that support Balinese culture, it means something will be lost Balinese culture.

Subak in Bali usually has a temple called Pura Uluncarik , or Bedugul Temple , which was specially built by the landowners

and farmers which destined for goddess prosperity and fertility goddess Sri . Because Balinese culture is closely related to agriculture. This can be seen from the more a lot land Agriculture transferred enable Becomes housing area, shops, industry and development tourist which causing land Agriculture neglected and even sacrificed for fulfil need community, so that productive agricultural land is decreasing and even finished in time upcoming, if over function land Agriculture the not controlled. Agriculture for Bali no only as source food and absorber of labor, but also a source of culture. In addition, subak as part of From Balinese agriculture, it has been made into a world cultural heritage, which is appropriate we take care and preserve its existence in the midst of rampant land use change occur.

Based on data from the BPS ( Central Bureau of Statistics) Bali Province in 2013, wide land province Bali which used for land ricefield reach

81.165 Ha (14.40 percent). Compared to the area of rice fields in 2012 which reached 81,625 Ha, which means a decrease of 460 Ha (0.56 percent). In another The non-rice field area reaches 274,402 Ha (48.68 percent) or more 98 Ha (0.04 percent), which previously reached 274,305 Ha (48.66 percent), this means that the land in Bali is still dominant (48.68 percent) is land not rice fields and a small part (14.68 percent) is rice fields, the occurrence of the conversion of rice fields in the province of Bali. Share from the agricultural sector in a broad sense from year to year continues to decline in 2013 share agriculture sector by 15.22 percent decreased to 14.64 percent in 2014, This decline is caused by one of them is the conversion of agricultural land to agricultural land non Agriculture. Happening over function land also caused fast developments in Bali, especially the development of the tourism sector which require infrastructure to support tourism. Besides that The development of the

population in Bali also greatly affects the growth population in Bali like seen on Table occu rrence of transfers function land, 1.1 following.

Table. 1.1

Bali Province Population Growth RateYear
2014

districts	Quantity Population Estimation			r
	2013	2014	2015
(1)	(2)	(3)	(5)	(4)
Jembrana	301.806	304,207	306,641	0.008
Tabanan	447,314	450,875	454.482	0.008
Badung	455,037	460.275	465,338	0.011
Gianyar	457,994	462,064	466.223	0.009
Klungkung	206.739	209.395	212.117	0.013
Bangli	256,846	258,390	259,940	0.006
Karangasem	532,903	539.022	544,951	0.011
Buleleng	796.168	802,726	809.148	0.008
Denpasar	607,324	612.803	618,318	0.009
Amount	4,062.131	4,099,757	4,136,655	0.009

Source : Ministry of Home Affairs SIAK data Year 2014

welfare level Bali from year to year has Based on the data in Table 1.1 the

increased, as reflected by GDP per capita. In population growth rate in the Province Bali

2013 Bali's GRDP per capita was Rp. 33.13 from 2013 to 2014 was 0.9 percent, if

million dan year 2014 as big as 38.11 observed per Regency/City, growth

million (On Base Price applicable), whereas population highest year 2013-2014 occur in

based on price constant year 2010 as big as Klungkung Regency is 1.3 percent,

Rp. 28,13 million on year 2013, in year followed by Karangasem district and

2014 increased to Rp. 29.67 million

Badung by 1.1 percent. With growth

(Statistics Official News, No. 13/02/51/Th. estimated at 0.9 percent contest so total

IX, 5 February 2015). Although occur over population Bali year 2015 estimated amount

function land Agriculture to non 4,136,655 inhabitants. Rapid development

Agriculture, growth economy Bali tourism in Bali is very much felt by the

permanent positive. Bali's economic growth Balinese, this can be seen from community

in 2014 grew 6.72 percent higher than in 2013 by 6.69 percent. From the production side, the highest growth was achieved by the Health Services and Social Activities Business Field by 12.43 percent. From side expenditure growth highest achieved by Component Export Goods and services which experience growth of 19.49 percent.

OVERVIEW LIBRARY

Source Power Land

Resource land is resource natural which very urgent for continuity life man because required in every activity humans, such as for agriculture, industrial areas, residential areas, roads for transportation, recreation area. Every human being does an activity, the source Natural resources are very important, without natural resources humans cannot biased activity. Land resources ( land resources ) as the environment Physical features consist of climate, relief, soil, water and vegetation as well as objects that exist in the area on it as long as it has an effect on land use. Therefore land resources can be

said to be an ecosystem because of the relationship between which dynamic Among organism which there is in on land the with environment (Mather, 1986).

Land has a special place in the resource group. because land is needed in all aspects of human life and land too become a major factor in influencing other natural resources. As resources, land has special characteristics in its allocation. Lots factor which influence Mark plot land like topography, fertility, location, method processing (source power man), and etc. From corner From an economic point of view, land can be interpreted as a whole good resource which character experience nor artificial which related with plot Earth surface. Knowledge economy too often refer land together with power work, capital and management as four factor production base. In In this sense, land is defined as a natural resource used in process production in produce food, fiber, ingredient building, ingredient mine or ingredient raw which required in life modern

(Didi                         Rukmana,

http://repository.unhas.ac.id/bitstream/handl e/ 123456789 /4009/

Babpercent        208percent20Source

percent20Powerpercent20Land.pdf ?sequence=1, accessed 16-9-2015).

Land have meaning urgent for para stakeholders which make use of it. Function land for public as the place stay and source of livelihood. For farmers, land is a source of production food and survival. For the private sector, land is an asset for accumulate capital. For the government, land is the sovereignty of a country and for well-being his people. Existence many interest which interrelated in land use, this results in overlapping overlapping interests between actors, namely farmers, the private sector, and the government in make use of the land. Agricultural land is land designated for agricultural activities. Agricultural land resources have many benefits for man. according to Sumaryanto and tahlim 2005 (in Puspasari, 2012), mentions that the benefits of agricultural land can be divided 99

into two categories. First, use values can also be referred to as personal use values. These benefits are generated from the results of exploitation or farming activities that conducted on source power land Agriculture. Second, non use values could also known as intrinsic values or innate benefits. The various benefits created with alone although no is destination from activity exploitation of agricultural land owners fall into this category.

Move Function Land

Utomo et al. (1992, in Hidayat et al., 2012), defines function transfer land or usually called as conversion land is change function part or whole area land from function beginning (like which planned) Becomes function other which Becomes impact negative (problem) to the environment and the potential of the land itself. Land conversion in the sense of changes/adjustments allotment use, caused by factors which broadly includes the need to meet the needs of the population which more increase amount and increase demands

will quality better life. The occurrence of land use change, especially land that is productive in the sense of land that is still in the future earning or producing, although result more small compared to with after transferred enable if seen from aspect economy. If something location occur conversion land Agriculture, quick land in surrounding will converted and nature tend progressive. in line with change structure economy which is characteristic development of a country or region, the need for land for non-profit activities agriculture is increasing from year to year. Trend This causes the conversion (conversion) of agricultural land to be difficult to avoided with say other every year certain occur conversion land. Wide the land conversion every year will be greater because of land conversion agriculture is generally contagious. In other words, once land conversion occurs in a location, the area of land to be converted at that location will increase large due to the associated land

conversion that occurred in the surrounding location, in additionalso power man (farmer) already very seldom process the land by professionals, because land which relative a little (farmer dirty), so that more many cost which issued when compared to with results which they get it in the agricultural sector and many young people are no longer working in the sector Agriculture. Change use land is increase something land use from one side of use to another is followed with the reduction of other types of land use over time the next, or the change in the function of a land at a different time (Wahyunto et al ., 2001, in Siswanto, 2006).

Development and Growth Economy

Wrong one indicator which very urgent in analyze Economic development that occurs in a country is economic growth. Basically, economic development and economic growth contain mean which different. Development economy on generally defined as something process which causing increase income real per capita population

something country in period long which accompanied by system institutional. As for economic growth interpreted as GDP increase or GNP regardless of whether the increase is greater or less than the rate of population growth, or whether changes in economic structure occur or no (Arsyad, 1999). Growth economy more pointing to change which is quantitative ( quantitative change ) and usually be measured with use data Product Domestic Gross (GDP or GDP) or income or final market value ( total market value ) of the final goods and services ( final goods and services ) resulting from an economy During period certain (one year).

Between economic growth and and economic development the two terms the meaning of change, growth is always used as a expression general which describes the level development something country, which be measured through percentage increase income national real. Term development economy usually linked with development economy in countries develop. With other 101

words, in mean term development economy, expert economy no just interested to the problem of the development of real national income , but also to the modernization of activities economy, for example to efforts to overhaul the traditional agricultural sector, the problem of accelerating economic growth and the problem of equalizing the distribution income (Sukirno, 2006).

Growth Economy

The theories of economic growth that have developed, among others, are as follows: following (Sukirno, 2006). This theory was pioneered by Adam Smith, David Ricardo, Malthus, and John Stuart Mills. according to theory this growth economy influenced by four factors, namely the population, the amount of capital goods, land and natural resources as well as the technology used. They put more his attention on influence increase population to growth economy. They assume that land area and natural resources and technology do not experience change. Theory which explain linkages Among income per capita with total

population called with theory population optimal. according to theory this, on at first increase population will causing increase in per capita income. But if the population continues to grow so law results more which less and less influence function production, i.e. marginal production will decrease, and will bring on state income per capita same with production marginal. On state this income per capita reach Mark which maximum. Amount population on time that named population optimal. If the population continues to increase beyond the optimal point, the population growth will cause a decrease in value economic growth.

Growth Population

The high rate of population growth in some parts of the world causes the population to increase rapidly, especially in developing countries. third world (developing) countries, the high population growth is very close relation with poverty. In a number of cleavage in world has occur poverty and food shortages. This phenomenon unsettled

the experts, and each of them trying to find the factors that cause the poverty. Generally, experts are grouped into three groups. The first group consists of adherents of the Malthusian school. Malthusian pioneered by Thomas Robert Malthus, and the Neo Malthusian school of by Garreth Hardin and Paul Ehrlich. Thomas Robert Malthus, a priest England, lived from 1766 to 1834. At the beginning of 1798 through his essay entitled Essai on Principle of Populations as it Affects the Future Improvement of society, with Remarks on the Speculation of Mr. godwin,

M. Condorcet, and Other Writers , states that residents (as well as plants and animals) if there are no restrictions, will grow multiply rapidly and fill quickly some parts of the surface Earth this (Mantra, 2003). height growth population this caused because connection sex between men and women cannot be stopped. In beside that Malthus believed that humans needed food to live. whereas rate growth ingredient food

far more slow compared to with rate growth population. If no held restrictions to growth population, so man will experience deficiency ingredient food. This is the source of human poverty and poverty. It is clear described by Malthus, as follows … Human species would increase as the number 1, 2, 4, 8, 16, 32, 64, 128, 256, and the substance as 1,2,3,4,5,6,7,8,9. in two centuries the population would be to the means of subsistence as 236 to 9; in three centuries as 4096 to 13 and in two thousand years the difference would be almost incalculable . To get out of the problem of food shortages the, growth population must be limited. according to Malthus restrictions the, could implemented with two method, that is preventive checks , and positive checks . Preventive checks , is subtraction population through birth suppression. Preventive checks can be divided into two, namely moral restraint and vice . Moral restraint (self-restraint), namely all efforts to curb sexual desire, and vice is the reduction of births, like abortion content, use tools 103

contraception, homosexual, promiscuity , adultery . For Malthus, moral restraint is restrictions the most important births, while the use of contraceptives has not could received (Mantra, 2003).

In the late 19th and early 20th centuries, Malthus' theory began debated again. Group which support Genre Malthus but more radical called with group NeoMalthusianism. according to group this (spearheaded by Garrett Hardin and Paul Ehrlich), in the 20th century (in the 1950s), the new world that at Malthus' time was empty is nowstart full with man. world new already no capable for accommodate quantity population which always increase. Paul Ehrlich in the book The Population Bomb in 1971, depicting the population and the environment in the world today as follows. Firstly, this world is already too many humans; second, the state of food ingredients is very limited; third, because there are too many people in this world, the environment has been polluted and damaged.

METHOD STUDY

Data and Method Election Sample

This study uses secondary data or time series data ( time series ). Data obtained from BPS Regency/City and BPS Province of Bali for the last 5 years. All data obtained are annual data from each Regency/City in the Province of Bali. During that time selected with consideration of limited data sources and time constraints which is available. The sample in this study is Regency/City which exist in province Bali.

Technique Analysis Data

This research uses panel data analysis or pooled data. Analysis using panel data is a combination of time series or time series data and crust latitude or cross section data. according to Gujarati (2003), for describe data panel by short, suppose on data cross section , the value of one or more variables is collected for several units sample at a time. Advantages of using panel data according to Hsiao (2003) compared to with time series and cross sections , is as

following.

• 1)       Panel data estimates can show

heterogeneity in each individual

• 2)       Data panel more informative,

more varied, reduce collinearity between variable, increase degrees of freedom and more efficient.

• 3)       Studies with data panel

satisfying for determine change dynamic compared to with repeated studies from cross section .

• 4)       Data panel more detect and

measure effect which by simple nocould measured by data time series or cross section .

• 5)       Data panel help studies for analyze

behavior which more complex.

• 6)       Panel data can minimize bias

generated by individual aggregations or company because data unit more many

Approach/Method Estimate Regression Data Panel

There are three kinds of approaches in panel data model analysis, namely common effect approach , fixed effect or random effect 104

approach or random effects .

• 1)       The common effect approach ,

which combines cross-section data with time series and estimation using the OLS ( Ordinary Least squares ).

Yit = o + i Xit + eit

Information:

i                   =  1,2. .. n

t                    =  1,2. .. t

n             = Number of cross section

t             = Amount time period

• 2)       Approach effect permanent ( fixed

effects )

The panel data procedure has several difficulties, among which are that the assumption of a consistent intercept and slope is difficult to fulfill. To overcome things the, which is conducted is to enter variable doll dan dummy variable so that different parameter values are good cross section nor time series could occur. Approach with using this dummy is known as the effect model or fixed effect or Least Square Dummy Variable (LSDV).

Yit = .i + Di Dit + Xi Xit + uit

Keterangan:

i                   =  1,2. .. n

t                    =  1,2. .. t

n             = Amount cross section t

= Amount period timee

= Variable bully

• 3)      Approach effect random ( random

effects )

Variable doll which entered in model effect permanent will could cause consequence. Addition variable doll the could reduce a lot degrees freedom which on finally will reduce the efficiency of the estimated parameters. The panel data model involve correlation between error term because change time which caused by differences in observations can be overcome with a model approach error component or also known as the error component model approach or also called with model random effect or random effect

Yit = i + i Dit + i Xit + itit = ui + vi + wit Information:

ui             = cross component section

errorvi         = time series error

component Wit = component combination error

Test Hausman

Test this conducted for test method which Very good used, whether fixed effect or random effect . Test using indicators

statistics Chi square count which for next compared to with chi square table to find out whether the null hypothesis is rejected or not . Where the null hypothesis of this test is that there is no relationship between the error is in a model with an independent variable, or Test statistic This Hausman following the Chi Square statistical distribution with k degrees of freedom , where k is the number of independent variables. If Hausman's stats value is more is greater than the critical value, then H0 is rejected and the right model is the model Fixed Effect On the other hand, if the Hausman statistic is less than Mark critical then the model right is the model Random Effect

Test Assumption Classic

Advantages study use data panel, is data which used to be more informative, the variability is greater, the collinearity lower among variables and many degrees of freedom (degrees of freedom) and more efficient (Hariyanto, 2005). Panel data

could detect and measuring impact with more good where Thing this no can conducted with cross method section and time series . Data panels allow for more complex learning about behaviorwhich there is in model so that testing data panel no need test classic assumption. With the advantages of panel data regression, the implications are not it is necessary to test the classical assumptions in the panel data model (Verbeek, 2000; Aulia, 2004; Wibisono, 2005; Gujarati, 2006; in Shochrul R, Ajija, et al.

2011).

Statistic test

Test this used for testing significance variable independent to variable dependent by Partial (test t) and Test F is used for test significance from all variable free as something unity, or measure the effect of independent variables together. Criteria used in this study is a two-way test in the level of significance = and degrees of freedom ( df) = nk, where n represents the number of

observation and k shows number of parameters including constants.

Definition Operational Variable

Variables which used in study this is variable independent (free) and variable dependent (bound ).

• 1)    The independent variable (free), is the variable that causes the emergence of or change variable dependent (bound variable). Independent variable which used in study this, is as follows.

• a)    Total Population (X 1 ), is population is the number of people who resides/domiciled in an area or area within study district/city in province Bali, have eye livelihood remain in the area, as well as legally registered under the applicable regulations apply in the area (in soul).

• b)    Share Agriculture To GDP (X2 ) , is ratio production sector Agriculture with total GDP district/city in province Bali (in percent).

• c)    GRDP Per capita (X 3 ), is Gross Regional Domestic Product (GRDP) shared with total population mid year which 107

stay in regencies/cities in Bali Province.

• 2)    Variable dependent, is variable which influenced or which Becomes result, because of the independent variable. The dependent variable in this study is the area of agricultural land (Y). Agricultural land is land intended for or suitable to be used as agricultural land to produce crops Agriculture especially rice in districts/cities in province Bali.

RESULTS AND DISCUSSION Development Land Ricefield in Bali

In 2013 from the total land area of Bali Province used for landricefield reach 81.165 Ha (14.40 percent). Compared to with wide land ricefield year 2012 which reach 81.625 Ha, means experience drop wide

460 Ha (0.56 percent). Part big wide land ricefield in Bali there is in Tabanan Regency which is Bali's "rice granary". Rice field area in Tabanan Regency reached 27.33 percent (22,184 ha) of the total paddy field covering an area of 81,165 ha. Then followed successively the next widest rice field are Gianyar Regency reaching 18.12

percent, Buleleng Regency 13.43 percent, districts Badung 12.50 percent and district/city other only has a rice field area of less than 10 percent, seen from the portion of land according to use in each region Regency/City, so districts Gianyar is the district with the largest percentage of rice field area which reached 39.96 percent, Tabanan Regency 26.43 percent of rice fields, Badung Regency 24.24 percent of paddy fields, Denpasar City 19.61 percent of land ricefield and districts other not enough from 15 percent the territory used as land rice field.District with region dominant land no ricefield is districts Bangli, Karangasem, Klungkung and Buleleng. Whereas districts with the territory dominant land no Agriculture is City Denpasar and District Jembrana ( http://bali.bps.go.id/ ).

Progress Speed Residents at Bali

Based on the data in Table 4.1, information is obtained that the density population in province Bali on year 2014 reach 727.63 people/km ² . This means that in every square kilometer of territory in the Province Bali is inhabited with population not enough more as much 728 person. If seen based on Regency/City, it turns out City Denpasar have ratio density population the highest, which was 4,942.76 people/km2, ^followed by districts Badung and Gianyar each 1,095.66 and 1255.61 people/km ² , while the lowest is Jembrana Regency of 361.38 people/km ² , high population density in Denpasar, Badung and Gianyar is inseparable from economic activities in three regencies and cities In addition to being the city center and tourism sector activities, so that trigger happening population urbanization

Table 4.1

Amount Population, Wide Region and Density province Bali Year 2014

districts	Wide	Population	Ratio Density
(1)	(2)	(3)	(4)
Jembrana	842	304,207	361.38
Tabanan	839	450,875	537.20
Badung	420	460.275	1,095.66
Gianyar	368	462,064	1,255.61
Klungkung	315	209.395	664.75
Bangli	521	258,390	496.13
Karangasem	840	539.022	642.04
Buleleng	1,366	802,726	587.70
Denpasar	124	612,803	4,942.76
Total Wide	5,634	4,099,757	727.63

Source : Ministry of Home Affairs SIAK data Year 2014

The population growth rate in Bali Province from 2013 to in 2014 of 0.9 percent, if observed per district/city, growth population highest year 2013-2014 occur in districts Klungkung, that is by 1.3 percent, followed by Karangasem and Badung districts at 1.1 percent. With an estimated growth of 0.9 percent per year, the total population Bali 2015 estimated to be 4,136,655 soul.

Growth Economy Bali

In 2014, the Bali economy was able to grow by 6.18 percent, compared to the previous year, growth this time it was recorded faster because on year previously economy Bali capable grow as big as 6.05 percent. Although growth Bali no reach

target which as big as 6.71 percentHowever, Bali's economic growth is far above the national level which only capable grew 5.02 percent during Year 2014.

Growth economy Bali year 2014 pushed by all sector economy except Mining and Quarrying which recorded a contraction of 0.61 percent. The sectors that experienced the highest growth were the Finance at 8.85 percent, followed by the Services sector which grew by 8.30 percent. Whereas sector other like Sector Agriculture grow 2.22 percent; the manufacturing sector grew 6.20 percent; electricity, gas and water sector clean grow 5.49 percent; sector building grow 2.98 percent; sector trading, hotel and restaurant grow 7.32 percent; sector

transport and communication grow 6.37 percent. Total Mark plus which created (GDP nominal/at current prices) in Bali in 2014 has reached Rp 106.25 trillion or up 12.37 percent from the previous year which is worth Rp 94.56 trillion.

As is known, nominal GDP is still an added value affected by price changes. So to see the added value in real terms (the development of production of goods and services in real terms) is determined by value added or real GDP/at constant price basis, which in 2014 value has reach Rp 36.94 trillion or go on 6.18 percent from year previously valued at Rp 34.79 trillion.

If you look at the economic structure of Bali, it is still dominated by the tertiary sector, because the service sector gives the largest role in the formation of the total added value the biggest. In detail, in 2014 the contribution of the agricultural sector was 16.45 percent; mining and quarrying sector 0.75 percent; industrial sector processing 8.68 percent; electricity, gas and

sector water net 2.18 percent; sector building 4.85 percent; trade, hotel and restaurant sector 30.14 percent; sector transportation and communication 14.28 percent; financial, leasing and service sectors company 6.86 percent; as well as sector services 15,80 percent. Or if grouped, donation sector primary reach 17,20 percent, sector secondary reach 15.72 percent and sector tertiary of 67.08 percent.

With achievements aggregate GDP nominal Bali in year 2014 worth Rp . 106.25 trillion, with the total population of Bali as a result of projections for the year 2014 which reach 4 million person more, so GDP per capita population Bali reaches Rp 25.9 million per capita/year or increase 11.04 percent if compared to 2013 which reached Rp.23.31 million per capita/year. Enhancement GDP per capita population Bali in a year final this at least reflects that the average productivity per person in creating added value has increased significantly. Growth GDP per capita

indicates how productivity achieved with utilization of technology, capital and labor, so that it becomes more effective and economic value.

Analysis Statistics Descriptive Variable Study

Descriptive statistics are used to see

an overview of the variables study. This study uses secondary data in the form of time series data and cross section data of Regency/City in Bali Province in the form of Rice Field Area(Y), Amount Population (X1 ) , GDP per Capita (X2 ) , and Share Agriculture To GDP (X 3) years 2010-2013

Table 4.2

Mean, Median, Mode, Std. Deviaton, Minimum, Maximum Jarque-Bera and Probability

criteria	Wide Land Ricefield (Y) (Ha)	Amount Population (X 1 ) (000) soul	GDP Per Capita (X 2 ) Rp.	Share Farm Against GDP(X 3 ) percent
mean	9,053.944	44,2634,2	17,172,150	22.27722
median	7,155,500	42.6450.0	15,629,180	26.73000
Maximum	2,2455,00	84.6200.0	35,633,410	33.67000
Minimum	2,506,000	17.100.0	10,431,597	6.110000
Std. Dev.	6,148.017	20,0654,1	5,954,641.	9.597106
Jarque-Bera	5.306696	1,730118	23,49273	4.946520
Probability	0.070415	0.421027	0.000008	0.084310
Observations	36	36	36	36
Cross sections	9	9	9	9

Source : Data processed

Based on Table 4.2, it gives an illustration that for the total data population is not normally distributed as seen from the value of probability Jarque-Bera of 0.421 is greater than the value of = 10 percent (95 percent confidence level), This means that there is a discrepancy very large (standard deviation) is relatively large when compared to with variable other, so that could concluded deployment population in Regency/City in province Bali is no equally.

Analysis Data Panel

Before conducting an overall panel data analysis, first carried out statistical testing for determine method what approach which will be used. Of the three existing approaches, the Pooled approach is used Least Square is felt to be inappropriate for the purpose of using panel data. By because that in study this only consider use approach effect permanent and effect random just. For

deciding is will use fixed effect or random effect then use test Haussman.

Setiawan and Endah (2010), suggest that panel data is a a combination of periodic data ( time series ) and individual data ( cross section ). Modeling with use technique regression data panel could conducted with use three approach alternative method processing. Approaches the that is, method Common Effect ( pooled least squares ), method Fixed Effect (FE), and method Random Effect (RE).

Metode Common/Pooled Least Square

The Common Effect method is a method that only combines data regardless of time and individual differences, it is assumed that behavior The data between Regencies/Cities in Bali Province is the same in various time periods. Results calculation with use program eviews 6, so output from regression use method Common Effect ( pooled least squares ), is as following.

Tabel. 4.3

Hasil Analisis Dengan Metode Pooled Least Squares

Dependent Variable: Y?

Method: Pooled Least Squares

Date: 09/30/15 Time: 06:19

Sample: 2010 2013

Included observations: 4

Cross-sections included: 9

Total pool (balanced) observations: 36

Variable         Coefficient Std. Error t-Statistic       Prob.

C	-21.82507
X1?	1.473662
X2?	2.113110
X3?	1.701096
R-squared	0.538392
Adjusted R-squared	0.495117
S.E. of regression	0.218435
Sum squared resid	1.526838
Log likelihood	5.803976
F-statistic	12.44098
Prob(F-statistic)	0.000015

4.729008     -4.615149 0.257996      5.711956 0.485289      4.354333 0.302973      5.614675	0.0001 0.0000 0.0001 0.0000
Mean dependent var	3.856324
S.D. dependent var	0.307416
Akaike info criterion	-0.100221
Schwarz criterion	0.075726
Hannan-Quinn criter.	-0.038811
Durbin-Watson stat	0.131705

Sumber : Hasil Analisis (2015)

Based on the results of the regression using the method Common Effect above it can be concluded, the independent variable (t-test probability ) which looks significant i.e. Total Population (X 1 ), GRDP Per Capita (X 2 ), and the share of Agriculture to GRDP (X 3 ). Results R2 ^_ ( Adjusted R-squared ) as big as 0.4951 or 49.51 percent

which means Total Population (X 1 ), GRDP Per Capita (X 2 ), and share of Agriculture to GRDP (X 3 ) is able to explain Y (Area Rice Fields), while remaining 40.49 percent explained by another factor.

Metode Fixed Effect

The Fixed Effect method is a method that estimates panel data with

use variable dummy for capture existence difference intercept. Method this assume that coefficient regression ( slope ) permanent between County/City in province Bali and between time.

Results calculation with using the program eviews 6, then the output of the regression using the method Fixed Effect (FE), is as follows.

Tabel 4.4

Hasil Analisis Dengan Fixed Effect

Dependent Variable: Y?

Method: Pooled Least Squares

Date: 09/30/15 Time: 06:28

Sample: 2010 2013

Included observations: 4

Cross-sections included: 9

Total pool (balanced) observations: 36

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	7.881739	1.710448	4.607998	0.0001
X1?	-0.623051	0.296948	-2.098183	0.0466
X2?	-0.040400	0.045272	-0.892393	0.3810
X3?	-0.191330	0.127918	-1.495728	0.1478
Fixed Effects (Cross)
_JEMBRANA--C	-0.120746
_TABANAN--C	0.546771
_BADUNG--C	0.172499
_GIANYAR--C	0.348828
_KLUNGKUNG--C	-0.458592
_BANGLI--C	-0.516817
_KARANGASEM--C	0.023364
_BULELENG--C	0.341989
DENPASAR--C	-0.337295

Effects Specification

Cross-section fixed (dummy variables)

R-squared	0.999739	Mean dependent var	3.856324
Adjusted R-squared	0.999620	S.D. dependent var	0.307416
S.E. of regression	0.005996	Akaike info criterion	-7.134229
Sum squared resid	0.000863	Schwarz criterion	-6.606390
Log likelihood	140.4161	Hannan-Quinn criter.	-6.949999
F-statistic	8361.478	Durbin-Watson stat	3.362146
Prob(F-statistic)	0.000000

Sumber : Hasil Analisis (2015)

Based on the regression results using the Fixed Effect method above, it can be concluded that the independent variable (t-test probability ) which looks significant is Total Population (X 1 ), while GRDP Per Capita (X 2 ) and share of Agriculture to GDP (X 3 ) is non significant . Results R2 ^_ ( Adjusted R-squared ) of 0.9996 or 99.96 percent which means the Total Population (X 1 ), GRDP Per Capita (X2 ) , and share Agriculture against GRDP (X 3 )

capable explain Y (Wide Land Ricefield), whereas the rest 0.04 percent explained by factor other.

Method Random Effect

The Random Effect method is a method that will estimate panel data where the disturbance variables may be interrelated over time and between individual. The results of the calculation using the program eviews 6, then the output from regression use method Random Effects (RE), is as following.

Table 4.5

Hasil Analisis Denngan Metode Random Effect

Dependent Variable: Y?

Method: Pooled EGLS (Cross-section random effects)

Date: 09/30/15 Time: 06:51

Sample: 2010 2013

Included observations: 4

Cross-sections included: 9

Total pool (balanced) observations: 36

Swamy and Arora estimator of component variances

Variable	CoefficientStd. Error	t-Statistic	Prob.
C	5.7415001.477821	3.885111	0.0005
X1?	-0.2493730.247652	-1.006947	0.3215
X2?	-0.0495520.042709	-1.160232	0.2545
X3?	-0.1024010.122872	-0.833397	0.4108
Random Effects (Cross)
_JEMBRANA--C	-0.064393
_TABANAN--C	0.516809
_BADUNG--C	0.157855
_GIANYAR--C	0.326066
_KLUNGKUNG--C	-0.339546
_BANGLI--C	-0.440283
_KARANGASEM--C	0.007708
_BULELENG--C	0.249726
_DENPASAR--C	-0.413943
	Effects Specification	S.D.	Rho
Cross-section random		0.242286	0.9994
Idiosyncratic random	Weighted Statistics	0.005996	0.0006
R-squared	0.106130 Mean dependent var		0.047714
Adjusted R-squared	0.022330 S.D. dependent var		0.006924
S.E. of regression	0.006846 Sum squared resid		0.001500
F-statistic	1.266465 Durbin-Watson stat		1.937526
Prob(F-statistic)	0.302425
	Unweighted Statistics
R-squared	-0.143900 Mean dependent var		3.856324
Sum squared resid	3.783625 Durbin-Watson stat		0.000768

Source : Results Analysis (2015)

Based on the results of the regression using the method Random Effect on could concluded variable independent (t-test probability ). Amount Population (X 1 ), GRDP Per Capita (X 2 ) and share of Agriculture to GRDP (X 3 ) all non-significant. The result of R2 ⁽ Adjusted R-squared) is 0.0223 or 2.23percent which means Total Population (X 1 ), GRDP Per Capita (X 2 ), and share of Agriculture to GRDP (X 3 ) is able to explain Y (Area Rice Fields), while the remaining 97.77percent explained by factor other.

Test Model Estimate

There are three panel data regression estimation methods, namely the Common Effect method ( pooled least square ), method Fixed Effect (FE), or method Random Effect (RE). Determining the panel method to be used in this study, then must

conducted a number of testing. Test Chow and Test Hausman is testing which can be used in determining whether the panel data model can be regressed by the Common Effect method, the Fixed Effect method, or the method Random Effects . The Chow test is used to determine whether the panel data model regressed by the Common Effect method or by the Fixed Effect method, if From the test results it was determined that the Common Effect method used, then it does not need to be retested with the Hausman test, but if the results of the test Chow the determined that method Fixed Effect which used, sothere must be a follow-up test with Hausman Test to choose between Fixed . method Effect or method Random Effect which will used for estimate panel data regression. The following is Table 4.6 which shows the results of the Test Chow.

Tabel 4.6 Uji Chow

Redundant Fixed Effects Tests Pool: DATA_P Test cross-section fixed effects
Effects Test	Statistic	d.f.	Prob.
Cross-section F	5305.502503	(8,24)	0.0000
Cross-section Chi-square	269.224300	8	0.0000

Cross-section fixed effects test equation:

Dependent Variable: Y?

Method: Panel Least Squares

Date: 09/30/15 Time: 06:34

Sample: 2010 2013

Included observations: 4

Cross-sections included: 9

Total pool (balanced) observations: 36

Variable	Coefficient	Std. Error       t-Statistic	Prob.
C	-21.82507	4.729008     -4.615149	0.0001
X1?	1.473662	0.257996      5.711956	0.0000
X2?	2.113110	0.485289      4.354333	0.0001
X3?	1.701096	0.302973      5.614675	0.0000
R-squared	0.538392	Mean dependent var	3.856324
Adjusted R-squared	0.495117	S.D. dependent var	0.307416
S.E. of regression	0.218435	Akaike info criterion	-0.100221
Sum squared resid	1.526838	Schwarz criterion	0.075726
Log likelihood	5.803976	Hannan-Quinn criter.	-0.038811
F-statistic	12.44098	Durbin-Watson stat	0.131705
Prob(F-statistic)	0.000015

Sumber : Hasil Analisis (2015)

Based on Table 4.6 the results of the Chow test, it shows that F-count > F-

table or 5305.502503 > 2.35 then H 0 is rejected and H 1 is accepted and the p-value (Prob.) significant, i.e. 0.0000 (less than 5 percent), so the method that used is method Fixed Effects . By because that, must conducted test advanced for determine method where which Very right to use between methods Fixed Effect or method Random effects , that is with do Test Hausman . Following is Table 4.7, which show results Test Hausman.

Table 4.7

Test Hausman

Correlated Random Effects - Hausman Test
Pools: DATA_P
Test cross-section random effects
Test Summary                  Chi-Sq. Statistic	Chi-Sq. d.f.	Prob.
Cross-section random                12.712841	3	0.0053
Cross-section random effects test comparisons:
Variable        Fixed        Random	Var(Diff.)	Prob.
X1?        -0.623051      -0.249373	0.026847	0.0226
X2?        -0.040400      -0.049552	0.000226	0.5422
X3?        -0.191330      -0.102401	0.001265	0.0124
Cross-section random effects test equation:

Dependent Variable: Y?

Method: Panel Least Squares Date: 09/30/15 Time: 06:56

Sample: 2010 2013

Included observations: 4

Cross-sections included: 9

Total pool (balanced) observations: 36

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	7.881739	1.710448	4.607998	0.0001
X1?	-0.623051	0.296948	-2.098183	0.0466
X2?	-0.040400	0.045272	-0.892393	0.3810
X3?	-0.191330	0.127918	-1.495728	0.1478

Effects Specification

Cross-section fixed (dummy variables)

R-squared	0.999739	Mean dependent var	3.856324
Adjusted R-squared	0.999620	S.D. dependent var	0.307416
S.E. of regression	0.005996	Akaike info criterion	-7.134229
Sum squared resid	0.000863	Schwarz criterion	-6.606390
Log likelihood	140.4161	Hannan-Quinn criter.	-6.949999
F-statistic	8361.478	Durbin-Watson stat	3.362146
Prob(F-statistic)	0.000000

Sumber : Hasil Analisis (2015)

Based on Table 4.7 the Hausman test results show that the Chi-squarecount < Chi-square table 12.712841 > 7.814728 then H 0 is accepted and H 1 is rejected,as well as p-value (Prob.) significant, that is 0.0053 (less than 5 percent), so that The method that will be used to estimate the model is the method Fixed Effects . 119

Results Estimate Model

LY= f (LX1,LX2,LX3,)

In this study, to determine the

effect of population (X 1 ), GRDP Per

Capita (X 2 ) and share of Agriculture to GRDP (X 3 ), then the model study which will be estimated, is as following.

Model on study the will estimated use 4 year time observation, that is from year 2010 until with year 2013. Model The estimation used is

regression as following:

Y_it = 7,882_it - 0,6231Xl_it

t                        (-2.09)

Sig.(prob.)             (0.04)

panel data with using the fixed method Effects (FE) . The use of the fixed effect approach is based on the results of the Chow test and Test Hausman which show that method fixed Effect more appropriate used in this study. Estimation results using the device EViews software 6.0 obtained equality results

- 0,0404 X2._t - 0,1913X3_it

(-0.89)                            (-1.49)

(0.38)                            (0.15)

Fh =             8361,478

Adj R2 ^_ =          0.999620

From these equations it can be explained that if each variable (Amount Population (X1 ) , GDP Per Capita (X 2 ) and share agriculture to GDP (X 3 ) experience change each as big as 1 percent so

• 1)    An increase in population (X 1 ) by 1 percent will reduce the area rice fields (Y) of 0.6231percent if the value of the independent variable others are considered constant

• 2)    An increase in GRDP Per Capita (X 2 ) by 1 percent will reduce the area rice fields (Y) of 0.0404percent if the value of the independent variable others are considered constant

• 3)    Enhancement share agriculture to GDP (X 3 ) as big as 1percent will reduce the area of rice fields (Y) by 0.1913percent if the value of variable independent other considered constant

Mark coefficient determination (Adjusted R-squared) as big as 0.9996 it

means that 99.96 percent of the total population (X 1 ), GRDP per Capita (X 2 ), and share agriculture to GDP (X 3 ) capable explain Wide Land Ricefield (Y), while the remaining 0.04 percent is explained by other factors. To prove Do the three independent variables really have a significant effect or not? non significant could proved with test statistics that is with test F (test simultaneous) and t-test (partial test). From the results of the analysis, it turns out that simultaneously Amount Population (X1 ) , GDP Per Capita (X2 ) , and share agriculture to GDP (X 3 ) significant capable explain land rice fields (Y), while in Partial only Amount Population (X 1 ) which significant and GDP Per Capita (X 2 ), and share Agriculture against GDP (X 3 ) nonsignificant .

Discussion

Switch function land is the switch function use land of sector Agriculture to sector non agriculture.Switch function

land the by live reduce total land Agriculture which there is County/City in province Bali. Especially in Bali development tourist which the more develop will push population from various area even world heading to Bali to work either to work in the tourism sector or sectors that are related to the tourism sector, so it is necessary to support facilities and infrastructure, especially settlements. Area of Bali Province is 5,636.66 km2 or 0.29 percent of the total area of the Republic of Indonesia Indonesia. by administrative province Bali divided on 8 (eight ) districts,

1 (one) city, 55 districts, and 701 village / village, whereas total population in 2014 based on registration data from the Ministry of Home Affairs' SIAK of 4,099,757 soul with rate growth as big as 0.9 percent per year, although rate growth population relative small However if seen from breadth and level population density in Bali 2015 was 736.7 people per Km ² ( http://bali.bps.go.id ).

according to http://www.kompasiana.com Bali is wrong one province

in Indonesia which is a tourism area. Many foreign tourists nor in country which visit for holiday or do activity business so that happen density population. When reviewed from population density data Total population of Bali Province according to the population census in 2000 was 3,146,999 spread over 9 districts and cities. Four census previously recorded the population of Bali in a row as follows: the 1995 census was 2,904,828 people, in the 1971 census it fell to 2,120,091 person, census 1980 notes 2,469,930 people and census 1990 increase Becomes

2,777,356 righteous- correct could said to have experienced enhancement. when our From a review, it turns out that the increase was caused by domestic immigrants who settled in Bali for business, many even came from abroad the permanent one in Bali because feel comfortable. Para immigrant the partMost of them have changed their ID cards to ID

cards in Denpasar or other districts they occupy. No only immigrant in country which doing Thing In this case, even foreign immigrants also helped make Denpasar ID cards or ID cards the district they occupy temporarily and renew their passports. Thing This becomes a problem regarding population density caused by uncontrolled migration. The Balinese people and government also tend to Be vigilant about catching the problem, so that later it doesn't interfere with security province Bali.

Increase GDP per capita is wrong one indicator increasing people's welfare. With increasing prosperity humans, they tend to improve the quality of their often need addition land for housing area. Beside that enhancement well-being also will push development facilities/infrastructure other office and shops which also need land. Need land the tend in take from land which still productive, although in analysis results study the effect still non significant, but

there are indications towards the reduction of paddy fields, ifseen from the sign of the coefficient which shows negative, there is a possibility in times coming Thing the can Becomes significant, like case population with a significant influence, the same thing also happened to variable share Agriculture to GDP which showing coefficient the direction negative, but not significant. The existence of land use change is indeed on a micro basis reduce the amount of rice production of farmers but overall instead land functions that have not caused food insecurity in Bali, such as other areas in Indonesia, but in the future it can be occur. With existence over function land on moment recently give impact which not yet are you serious to vulnerability food, However if the more a lot of land conversion to the non-agricultural sector will result in low food security.

Switch function land could causing unemployed new in the

agricultural sector, this is because at the	Agriculture, specifically land Agriculture
time of land conversion to non-agricultural	ricefield.    Wide    land    Agriculture
sector then some people will lose a new	productive which switch function keep
livelihood. While other sectors may not	going increase and not controlled, which
necessarily accept it due to lack of	will result in occur drop production food
expertise which exists. Total poverty rate	and  threaten  endurance   food  and
of the population working in the	sovereignty food, whereas need food
agricultural sector may increase due to	population the more big because existence
land use change. This happened because	population growth is also getting bigger.
part from they will lost eye her livelihood,	Then there will be inequality between the
so that their income by automatic also will	means of satisfying needs and increasing
is lost. Vulnerability food region is a	needs, this is evidenced by the very
condition where in the area most of the	significant influence of the population on
household residents do not could fulfil 70	the area paddy fields, although the per
percent energy sufficiency and protein for	capita GRDP which is a reflection of level
growth   normal   physiology.   Food-	well-being public by general and share
sufficient areas have potential for housing	Agriculture to GDP, not yet have
the household is food insecure. The term	influence which significant, but already
food insecurity does not mean that it	there is signsin a significant direction seen
occurs deficiency food in the area.	from the slope and from the negative
CONCLUSION DAN SUGGESTIONS	coefficient, which means an increase in
Uncontrolled and excessive land	GRDP per capita will lead to a decrease in
use change is already happening of course	the potential of the area agricultural land.
will impact negative for time front	As for suggestion which could 124

given from writing paper this, is as following.

• 1)       Government to be more serious

in responding to problems related to over function land, special land Agriculture (ricefield) main in establish a policy and legislation in the context of maintain food security and sovereignty food.

• 2)       Public should realize importance

land Agriculture specifically agriculture (rice fields) to meet the food needs of the current population andin times future.

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