VALUATION IRRIGATION OF RICE FARMING AT UPSTREAM AND DOWNSTREAM AREAS IN SPECIAL REGION OF YOGYAKARTA

  Department of Agribusiness, Faculty of Agriculture Universitas Muhammadiyah Yogyakarta

  Jl. Lingkar Selatan, Kasihan, Bantul Regency, Yogyakarta

  

VALUATION IRRIGATION OF RICE FARMING AT UPSTREAM

AND DOWNSTREAM AREAS IN SPECIAL REGION OF

YOGYAKARTA

  Habibullah

  1*

  , Triyono

  

1

  , Aris Slamet Widodo

  1 1)

  International Conference on Agribusiness Development for Human Welfare 2016

• corresponding author:

ABSTRACT

  

This study aims to know Willingness To Pay (WTP) farmers for management and

maintenance of irrigation and factors that influence it on rice farming at upstream

and downstream areas in Special Region of Yogyakarta. Survey is conducted to 60

respondents, 30 farmers at upstream area and 30 farmers at downstream area.

Primary data obtained through questioners and interviews, and then analyzed using

multiple linear regression and descriptive analysis. Analysis results show that the

WTP average amount of Rp17.500,- at upstream area and Rp11.167 at downstream

area. Willingness to pay is influenced significantly by family size, wide land area,

irrigation management services, quality of irrigation water and location. There are

some farmers in downstream area that will not pay for the irrigation. They opine the

water is already in nature as God’s present.

  Keywords: valuation, willingness to pay (WTP), irrigation, rice farming

  INTRODUCTION

  Agriculture Ministry (2013) issuing to increase crop production especially for rice farming 2,3% per year. That target could be achieved by increasing farming productivity with land intensification. Intensification could be increased by optimizing production inputs. One of that inputs is to hand over availability of irrigation water, especially at wet land farming. That statement is agreed by U.S Environmental Protection Agency (2012) with statement,

  “Irrigation makes agriculture possible in areas previously unsuitable for intensive crop production”. In a row with previously statement, Agriculture Ministry (2013) in framework of developing main food crop production give an assignment to Unit of Echelon 1, as part of General Directorate of Infrastructure and Tools to execute developing agricultural irrigation in Indonesia.

  Province of Special Region of Yogyakarta (2013) has wide wet land in amount of 56.539 acre. The land spread in some areas with wider wet land located in Sleman and Bantul Regency. Based on area characteristic Sleman Regency is located closer with water irrigation sources, so it could be called as upstream area of water irrigation in Special Region of Yogyakarta. The irrigation water flow to various areas in Special Region of Yogyakarta, one of area is Bantul Regency which it has second wider wet land area after Sleman. Based on irrigation flow, Bantul could be called as downstream area.

  Stability and good sanitation are influenced by irrigation canal infrastructures and tools, with sustainable management services. Indonesia government (1974) and Special Province of Yogyakarta government (2014) ordinance about irrigation explain that farmers have to participate in maintenance and treatment on the process of irrigation. According to Syaukat and Siwi (2009) explain that irrigation needs an expense to keep its sustainability. But in field, mostly irrigation funding does not appropriate with farmers willingness to pay. It causes burdening farmers economy. Therefore, to support it is needed field survey about farmers

  Habibullah, Triyono, Aris Slamet Widodo

  (%)

  50 1 3,33 1 3,33 6 > 50

  40 1 3,33 5 40 -

  5 30 -

  13 43,33 4 20 - 30 1 3,33

  40 3 10 - 20 17 56,67

  12

  30

  10

  10 2 < 10

  3

  1

  (%) Total (person) Total

  willingness to pay (WTP) for sustainable management and maintenance of irrigation.

  Upstream Downstream Total (person) Total

  No Interval WTP (000, Rp/GS)

  Based on the above data known that mostly values of willingness to pay (WTP) at upstream and downstream areas ranging from Rp10.000,- to Rp20.000,- per growing season. The data indicate there are only small proportion (13,337% at upstream area and 6,667% at

  Source: Primary data processed Source: Primary data processed

  Table 1. Willingness to pay farmers distribution of rice farming for management and maintenance of irrigation at upstream and downstream areas in Special Region of Yogyakarta, 2015

  Willingness to pay farmers for management and maintenance of irrigation describe the level of willingness of farmers' participation in ensuring the sustainability of irrigation in farming areas in order to empower independent farmers. The independent farmers will assist the government in giving aid that precise target, so the costs for management and maintenance of irrigation from government can be accommodated by irrigation expense contribution of farmers. Willingness to pay farmers distribution of rice farming at upstream and downstream areas in Yogyakarta can be seen in the following table.

  RESULT AND DISCUSSION Willingness To Pay (WTP)

  Location determination is chosen using purposive method. Purposive method is used by consideration that water of the irrigation in the downstream area is flowed from water irrigation in the upstream area, therefore the both irrigation canal have one water source. This study took samples of each irrigation areas in upstream and downstream as many as 5 farmers as respondents with simple random sampling non proportional technique. The overall number of samples in this study is 60 farmers.

  METHOD This study use descriptive analysis.

  This study aims to know farmers Willingness To Pay (WTP) for management and maintenance of irrigation, and the factors that influence it on rice farming at upstream and downstream areas in Special Region of Yogyakarta.

  Based on earlier study willingness to pay for management and maintenance of irrigation is influenced by many factors. According to Alhassan, et al (2013); Cho, et al (2008); Arifah (2008) explain that the factors influence WTP consist of farm land location, ownership of land farm, land lease prices, income, knowledge, and farmer age. According to Hershey (1993) that water quality and management are also important factors for irrigation process. Then, the both factors should try analyzed as new factors that affect to farmers WTP.

  This study use Contingent Valuation Method (CVM) to get the value of WTP. This technique is explained by Suparmoko, et al (2014 and has been used in study of Misra, et al (1991), Tresnadi (2000), Norwood, et al (2005), Whitehead (2006), Weldesilassie, et al (2009), they use CVM as a method to determine value of goods and service which it are not marketable. To get the price of environmental cost could be got by respondents preference toward to non- market natural resource with give question about Willingness To Accept (WTA) or Willingness To Pay (WTP) as substitute merit loss or as to defend and increasing services of natural resource.

  2 6,67 Total 30 100 30 100

  International Conference on Agribusiness Development for Human Welfare 2016

  downstream) are willing to pay irrigation funding more than Rp20.000,- per growing season. It means that if applied irrigation funding more than Rp20.000,- it will burdensome farmers economy.

  If the value of WTP both areas compared, the average value of WTP in upstream area is greater than downstream area. The upstream area has average value of WTP in amount of Rp17.500,-, and at downstream area only about Rp11.167,-. This value is derived by the total middle interval values of WTP divided by the total of respondents. From the value can be seen there are differences WTP value in both regions amount of Rp6.333,-.

  The above data also shows that in downstream area amount 10% of farmers which have value of WTP amount of Rp0,- . It means that farmers do not willing to pay irrigation funding. Upon further interviewed exploration, the farmers claimed that water is already available in nature, then they opined that they do not need to pay cost for management and maintenance of irrigation. The presumption is classified on human attitudes that consider water resources as free in take or given from God which illustrated as paradoxical water pearl by Hartwick and Ollewiller (1997) in Arifah (2008) This attitude should to be educated for the sustainability of irrigation water resources.

  If viewed by farmer willingness to be part of workers to manage and maintain the irrigation in both areas can be seen in the following table.

  Table 2. Distribution of willing to participate of farmers as workers to manage and maintain the irrigation, 2015

  No Irrigation Area Willingness To

  Participate Yes (percent) No

  (percent)

  1 Upstream 93,334 6,667

  2 Downstream 96,667 3,334

  Source: Primary data processed Based on the above table known that almost all farmers are willing to participate as worker to manage and maintain the irrigation. It means that without other or government participation farmers would still treat the irrigation for sustainability on his farming. According to result of interviewed, the management and maintenance of irrigation independently that using farmers as workforce has become a habit for a long time. The spirit of cooperation emerged because of the encouragement and farmers' awareness to manage and maintain the sustainable irrigation. To manage and maintain the irrigation usually instructed by farmers group management that known as P3A group, or by initiation of farmers with group agreement.

  Some small farmers are not willing to manage and maintain the irrigation. They mention the reason that irrigation already has their own management, so the farmers claim that they do not need to participate as its worker. Other farmer claim that he will not participate because he is already too old, but he willing to pay irrigation funding higher than other farmers or to provide food while other farmers manage and maintenance irrigation.

  The Factors that Influence the Willingness To Pay (WTP) for Management and Maintenance of Irrigation

  Willingness to pay is influenced by many factors. The factors that affect WTP can be used as a reference to collect irrigation funding with attention to the factors influence it in order to alleviate economy load of farmers. Based on analysis, WTP is influenced by the following factors that can be seen in the following table. To know the factors that influence WTP can be analyzed by multiple linear regression (Supranto, 2001).

  Habibullah, Triyono, Aris Slamet Widodo

  3 Level of education 582,838 1,129 0,264

  9 Ownership of land farm -3301,242 -851 0,399

  8 Irrigation water quality -2953,998 -2,112 0,040**

  7 Irrigation management services 1260,186 1,973 0,054*

  6 Wide land area 2,586 2,372 0,022**

  5 Farming experience 224,434 1,544 0,129

  4 Family size 2001,727 2,019 0,049**

  2 Age -262,699 -1,099 0,277

  Table 3. Factors that influence willingness to pay (WTP) farmers on rice farming irrigation at pstream and downstream in Yogyakarta Source: Data processed consist of coefficients, the model summary, and analysis of variance Note: * = Significant at α = 5%, ** = Significant at α = 10%

  1 Constant 3769,858 0,212 0,833

  No Model Coefficient t-count Sig

  Family size has a coefficient amount of 2001,727 with the direction of positive relationships. It means if the family size is increased amount of the unit then will increase the value of willingness to pay amount of Rp2.001,727,-. In the case, family size can causes positive and negative impact. The positive impact

  The wide land area has a coefficient amount of 2,586 with the direction of positive relationships. It means that if the wider land area amount of the unit, the value of willingness to pay will increase amount of Rp2.586,-. Based on these data it is known to increase the value of WTP, the wide land areas have to be improved.

  Location has a coefficient amount of 10.662,694 with the direction of positive relationships. Location is a dummy variable, in this case the upstream area indicated by the value 1 and the downstream area value 0. Analysis result shows the value of WTP in upstream area is higher than the downstream area with a difference amount of Rp10.662,694,-. This indicates that each region has a different WTP each other.

  Based on the distribution of the t- table at α= 5% is known t-table amount of 2,007, while the value t-count of four variables above have a value higher than t-table. The variables are family size, wide land area, irrigation water quality, and location. Furthermore, there is one variable that has a value significantly below α= 10%, it is irrigation management services. Based on the distribution t-table at α = 10% is known amount of 1.675, while the t-count value of irrigation management service variable has a value higher than t-table that is equal to 1.973. Then, the decision taken is to accept H0 and reject Ha. It means as partially WTP is influenced significantly by family size, wide land area, irrigation water quality, irrigation management services, and location.

  In comparison of value of f-count and f-table, known that value of f-table at α = 5% amount of 2.069, while the above data shows the value of f-count is greater than f-table that is equal to 3.348. The decision taken is to accept H0 and reject Ha. It means the willingness to pay is influenced simultaneously by age, level of education, family size, farming experience, wide land area, irrigation management services, irrigation water quality, ownership of land farm, and location. Partially, WTP is influenced significantly by family size, wide land area, irrigation water quality, irrigation management services, and location.

  10 Location 10662,694 2.712 0,009** R = 0,613 R-Sq = 0,376 R-Sq (adj)= 0,264 Analysis of Variance df = 59 F-count = 3.348 Sig. = 0,003

  Willingness To Pay Petani Terhadap Peningkatan Pelayanan Irigasi Melalui Rehabilitasi Jaringan Irigasi (Studi kasus: Daerah Irigasi Cisadane-Empang, Desa Pasir Gaok,

  2. WTP is influenced by the location, wide land area, family size, irrigation management services, and irrigation water quality.

  Agricultural Science. V (4): E-ISSN 1916-9760. Arifah, Fitria Nur. 2008. Analisis

  Estimating farmers willingness to pay for improved irrigation: An economic study of Bontanga Irrigation Scheme in Norther Ghana. Journal of

  Alhassan, M.; J.Loomis; M.Frasieer; S.Davies; A.Andales. 2013.

  REFERENCES

  I gratefully acknowledge the heartiest to Mr Triyono, SP., MP who help this study (Data, references, costs, time and moral support) and also to Mr Dr. Aris Slamet Widodo, SP., MSc, he provided guidance and assistance in the midst of his busy activity.

  ACKNOWLEDGMENT

  Based on the above conclusions, therefore suggested that the establishment of irrigation funding should pay attention to the factors that influence WTP, especially to wide land area, family size, irrigation management services, and the irrigation water quality.

  1. The average willingness to pay (WTP) at upstream area amount of Rp17.500,- and in downstream area Rp11 167,- or mostly ranging on Rp10.00-20.000 by the WTP interval.

  International Conference on Agribusiness Development for Human Welfare 2016

  Based on the results of the discussion above conclusions are derived as bellow.

  CONCLUSION

  Then from the above data can be made a multiple linear regression model by response variable the value of willingness to pay. The model equations are structured as below: WTP = 3769,858

  Irrigation management services have a coefficient amount of 1260,186 with positive relationship. It means the better irrigation management services amount of the unit indicator, then the WTP contributions will increase amount of Rp1.260,186. Therefore, increasing irrigation management services will increase WTP value.

  The irrigation water quality has a coefficient amount of -2953,998 the negative relationship. It means that if a quality of irrigation water in worse per unit indicator then WTP will increase amount of Rp2.953,998. This happen because the quality of irrigation water can affect to the farm process, so that if the water quality is getting worse, the famers hope to improve the quality, by increasing the cost to repair the water quality.

  Therefore, in this study possibly the family size is consist of productive people which they help farming expense to increase sustainability farmers farming.

  happen if the family size is consist of productive people then the source of income or farmers’ economic conditions will increasing better, so the cost for farming will become more bigger. In negative side, if the family size is consist of non productive people, then it will be burden that complicate farmers economy.

• – 262,699 Age + 582,838 level of education + 2001,727 family size + 224,438 farming experience + 2,586 wide land area + 1260,186 irrigation management service - 2953,998 quality of irrigation water – 3301,22 ownership of land farm dummy + 10662,694 location dummy. The regression coefficient served to explain the effect of each factor. The data shows the determination coefficient amount of 0,264. This value indicates the value is explained by the ninth WTP variables (Age, level of education, family size, farming experience, wide land area, irrigation management services, quality of irrigation water, ownership of land farm and location) amount of 26,4%, while the remaining 73,6% is explained by other factors which not included on the model.

  Habibullah, Triyono, Aris Slamet Widodo Kecamatan Rancabungur, Tresnadi, Hidir. 2000. Valuasi komoditas Kabuapten Bogor, Jawa Barat). Intitut lingkungan berdasarkan contingent

  Pertanian Bogor, Bogor. valuation method. Jurnal Teknologi Badan Perencanaan Pembangunan Lingkungan. I (1): 38-53. Nasional. 2013. Proyeksi Penduduk United States Environmental Protection Indonesia 2010-2035. Badan Pusat Agency, 2012. Irrigation (Online). Statistik, Jakarta. www.epa.gov.html diakses

  31 Cho, S.H.; S.T.Yen; J.M.Bowker; Januari 2015. D.H.Newman. 2008. Modeling

  Weldesilassie, A.B.; O.Frӧr; E.Boelee;

  willingness to pay for land S.Dabbert. 2009. The economic conservation easements: Treatment value improved wasterwater irrigation of zero and protest bids and a contingent valuation study in Addis application and policy implications. Ababa Ethiopia. Western Agriculltural

  Journal of Agricultural and Applied Economics Association. XXXIV (3): Economics. XL (1): 267-285. 428-249. Hersey, D.R.1993. Evaluation of irrigation Whitehead,, J.C. 2006. Improving

  water quality. University of California Willingness to pay for quality

  Press. LV (4):228-232. improvements through joint Misra, K.S.; C.L. Huang.; S.L. Ott. 1991. estimation with quality perceptions.

  Consumer willingness to pay for Southern Economic Association. pestiside-free fresh produce. Western LXXIII (1):100-111

  Agricultural Association. XVI (2): 218- 227. Norwood, F.B.; R.L.Luter; R.E.Massey.

  2005. Asymetric willingness to pay distributions for livestock manure. Western Agricultural Economic Association. XXX (3): 431-448. Republik Indonesia. 1974. Undang-

  undang Republik Indonesia No 11 Tahun 1974 tentang pengairan.

  Menteri Sekretaris Negara, Jakarta. Republik Indonesia. 2006. Peraturan

  Pemerintah Republik Indonesia No 20 Tahun 2006 (Online).

  diakses 19 Juni 2015. Suparmoko, M.; D.Sudirman; Y.Setyarko;

  H.S.Wibowo. 2014. Valuasi ekonomi neraca sumberdaya alam hlm. 35-54. Dalam Valuasi Ekonomi Sumberdaya

  Alam & Lingkungan. BPFE, Yogyakarta.

  Supranto. 2001. Analisis regresi ganda:

  Statistik teori dan aplikasi. Erlangga; Jakarta.

  Syaukat, Y. & A. A. N. Siwi. 2009.

  Estimating The Economic Value of Irrigation Water on Rice Farming System in Vander Wijceirrigation Areas, District of Seman, Yogyakarta.

  Jurnal Ilmu Pertanian Indonesia XIV (3):201-210.

  International Conference on Agribusiness Development for Human Welfare 2016

  Valuation Irrigation Rice Farming at Upstream and

  Downstream Area in Special Region of Yogyakarta Habibullah, Triyono, Aris Slamet W

  The study aims to WTP farmer for management and - maintenance of irrigation. This paper hasn’t been clear enough in stating the measurement whether is Rp/m3 or

  QUESTION else?

• What is the reasoning behind argumentation that family size able to influence WTP? Is quality of irrigation water variable’s impact really based on certain theories? The measurement of WTP is Rp/ Growing season - The quality of irrigation water variable’s impact negative

• ANSWER to WTP. Family size is negative impact, if the family

  members are not productive. Low education and unemployment. Please explain some reasons in more detailed why such - as family size effect the WTP

  SUGGESTION

  The conclusion should be clear, which variables are - positive influenced and which variables are negative influenced.

  International Conference on Agribusiness Development for Human Welfare 2016

  

RICE FARMER’S PERCEPTION AND ITS EFFECT TOWARD

  Ashari*, Juwaidah Sharifuddin, Zainal Abidin Mohammed, Rika Terano Department of Agribusiness and Bioresource Economics,

  Universiti Putra Malaysia, Serdang Selangor 43400

• corresponding author: ashari_sp@yahoo.com

  

ABSTRACT

Although the organic farming has a good prospect in future, the rate of its adoption

is still slow. Based on literature studies reveal that perception toward innovation

characteristics has a significant contribution toward adoption. The main objective of

current study is to examine the farmer’s perception namely perceived of usefulness

(PU), perceived risk (PR), environmental awareness (EN), and also attitude (AT) and

their effect on the behavioral intention. This study involves 600 rice farmers as

respondents in Sragen District, Central Java. The respondent is grouped into two

categories namely semi organic and conventional farmer and the data were obtained

through a structured questionnaire. The results show that in case of semi organic

farmer, all of variables have positive effect on intention exceptional for PR. Each of

variables is significant at 0.01 levels but for EN is not significant. The coefficient

determination (R ² =0.485) implies that 48.5% of the variance in intention is explained

by the variation of four variables. Meanwhile, in term of conventional farmers indicate

the similar result in sign of direction. But, all of variables are significant at 0.01 level

with R ² =0.596. The overall test (F-test) exhibits that set of independent variables

jointly significant toward behavioral intention at 0.01 levels. As conclusion, it is

obviously that the perceptions and attitude have significant effect toward intention.

Therefore, the effort should be undertaken to raise a positive farmer’s perception.

Farmer also needs a support from several parties to encourage them for engaging

in organic farming practice.

Keywords: organic farming, farmer’s perception, adoption process, behavior intention

  INTRODUCTION

  The year 1992 became an historic event in the Southeast Asia region, because such year was signed of the ASEAN Free Trade Agreement (AFTA) in the ASEAN Summit in Singapore. The aim of AFTA was to create a single market and a world production base through the elimination of tariff and non-tariff constraints with the underlying goal of enhancing competitiveness with ASEAN countries. There are three pillars of the AFTA as agreed by the ASEAN leaders and they are interlinked with each other namely ASEAN Economic Community (AEC), ASEAN Political-Security Community and ASEAN Socio-Cultural Community (Anonymous, 2016).

  Further, in 2003 in Bali, ASEAN leaders agreed to establish the ASEAN Economic Community (AEC) in 2020.

  Four years later, the aim was reaffirmed at a meeting in 2007 with an accelerated timeframe of 2015. Eventually, the AEC have implemented on December 31, 2015 with an underlying agenda of economic integration of ASEAN countries to eliminate or minimize the obstacles in economic activity across the region, in trade, goods and services, and investment.

  The implementation of AEC is hopefully able to accelerate the economic growth for each member, including Indonesia. As one of the important sector, agriculture is supposed to grab the chance through the increased of trade. The high value commodity (product) has potential to meet this goal, for instance the organic product. The emergence of awareness among consumers about healthy food and environmental-friendly Ashari, Juwaidah Sharifuddin, Zainal Abidin Mohammed, Rika Terano

  practicing enable to raise organic product demand in ASEAN countries. Besides, the growth of organic market in developed countries also provides an opportunity for Indonesia to gain the advantage.

  Although organic food has a good prospect in the future; but farmer’s interest in practicing organic farming is relatively low which is indicated by slow adoption rate. The question is, why the farmers are “reluctant” to adopt organic farming that constitute as an innovation? Rogers (2003) proposed that farmer’s perception toward innovation characteristic/attributes is very critical in adoption. Thus in this context farmer’s perception on organic farming is essential. It means that if they perceive that an organic farming has many advantages, the adoption process will be easier and vice versa.

  Further, according to Rogers (2003) the adoption is about a decision-making process. Therefore, farmers go through a stage or some stages of being aware or knowledgeable of organic farming related technology, to forming positive or negative perception toward organic farming. He mentioned there are five characteristics of innovations those are: relative advantage, compatibility, complexity, trialability, and observability. Indi viduals’ perceptions on such characteristics will determine the rate of adoption. Meanwhile, Davis (1989) who proposed the theory of Technology Acceptance Model (TAM) has formulated simpler characteristics of technology, namely perceived usefulness (PU) and perceived ease of use (PEU). PU affects to behavioral intention for adoption a certain technology directly or through the attitude as mediator. In addition, the results of case study by Wang and Liu (2016) demonstrated that attitude (both cognitive and affective) also positively influence on behavioral intention.

  In particular, organic farming is closely related to environmentally friendly lifestyle. Lampkin and Padel (1994) stated that organic farming was perceived as part of the solution to environmental degradation. Meanwhile, Anderson (1995) claimed that environment concern and health problem emerged by conventional practice has contributed a significant role in forming the sustainable agriculture movement. Maurer (1997) in Khalidi et al (2007) found environmental rationale were important for conversion and the improved social acceptance of organic farming. Thus, for farmers who are more awareness on environmental concern will have a higher intention to engage in organic farming.

  Further, the adoption of technology process usually encounters an uncertainty. Thus, the perception of risk against technology also influences the adoption behavior especially for small farmers. Berry (1984) stated that small farmer more susceptible incurred the risk. The higher of farmers’ perception on the risk will reduce their perception toward technology’s advantages (Gefen et al in Horst et al 2006). According to Padel (2001) the low risk of technology is one of the characteristics that should be fulfilled by an innovation in order to be adopted easily.

  In order to comprehend the process of adoption on organic farming, it requires seeking the factors affecting the adoption process. By assessing these factors will be fruitful to formulate the strategy in accelerating the adoption rate among farmers. The purpose of study is: (1) to explore the perception and attitude of farmers toward organic farmer; and (2) to examine the effect of perception and attitude on behavioral intention to adopt organic farming.

  METHOD Research Location and Sampling Procedure

  The study is conducted in Sragen District, Central Java Province, Indonesia. This district is selected as research location by considering as the center of organic rice farming and it has potency to grow steadily. In such district, the certified organic rice farmer actually has been existed; however, most of farmers constitute conventional farmer and as well as semi-organic farmer. Since the objective of study is related to behavior intention to adopt organic farming, d.f. in the numerator and n - p - 1 d.f. in the denominator. If the test results reject H , it means that at least one or all of independent variables affect the dependent variable or statistically significant. In other words, the models is “good” to predict the influence of the independent variables towards the dependent variable. Conversely, if the test results accept H , implies there is no independent variables that affect behavioral intention. Thus, the model is inappropriate to predict the influence of independent variables against dependent variable (Gujarati, 2002)

  F a is based on an F distribution with p

  3 AT + β

  equal to zero In association with F test, the rule is reject H if p-value < a or if F > F a , where

  H : b 1 = b 2 = . . . = b p = 0 H a : One or more of the parameters is not

  To examine the goodness of model, the significance test will be employed. There are two types of such significant test, namely F Test dan t test. The F test is used to determine whether a significant relationship exists between the dependent variable and the set of all the independent variables. The F test is referred to as the test for overall significance. The hypotheses will be tested is:

  Significance Test

  Based on the model specification, the sign of coefficient in each of independent variables will supposed to be: β1 > 0, β2 < 0, β3 > 0, β4 < 0. These mean that the perceived usefulness, environmental concern, and attitude are expected to affect positively toward behavioral intention. Conversely, the perceived of risk will influence negatively on behavioral intention.

  Where: BI = Behavioral Intention PU = Perceived Usefulness EC = Environmental Concern AT = Attitude PR = Perceived Risk µt = error term,

  4 PR

  2 EN + β

  International Conference on Agribusiness Development for Human Welfare 2016

  1 PU + β

  Model specification was formulated in the multiple linear regressions and written as follows: BI = β + β

  Data were analyzed descriptively using mean in term of perceived usefulness, environmental concern, perceived risk, attitude, and behavioral intention. To measure the extent of perceived and attitude level employed the Likert Scale with a range of 1 (strongly disagree) to 7 (strongly agree). The higher mean score implies the higher perception of the variable in question. All of these variables are latent/construct; hence, each construct will be described by some measurement variables. Meanwhile, inferential statistical test is performed to determine the relationship between perceived and attitude (as independent variables) to behavioral intention (dependent) using multiple linear regressions with ordinary least squares (OLS).

  Data Analysis

  The selection of respondents is undertaken by multistage sampling method. In the first step, of 8 sub-districts as main producer area of rice are selected randomly to obtain 5 sub-districts. Based on selected sub-district, and then select randomly 2 villages for each of sub- district. After the villages identified, afterwards generate sampling frame by listing all of the farmers both semi organic and conventional farmer in selected village. To determine the respondents, the systematic random sampling is employed. In each of village, as many as 30 semi- organic and 30 conventional farmers are selected as respondent. Therefore, the total respondent is 600 farmers consist of 300 semi organic and 300 conventional farmers. Data collection process carried out by face-to-face interviews using a structured questionnaire

  Sampling Technique

  therefore, the selected respondent exclude the organic farmers; instead the semi organic and conventional farmer.

• μ

  Ashari, Juwaidah Sharifuddin, Zainal Abidin Mohammed, Rika Terano

  Meanwhile, the t test is used to is rejected H0, implies the variables tested determine whether each of the individual have significantly effect on the dependent independent variables is significant. A variable or statistically significant. In separate t test is conducted for each of the contrast, if the test results accept H0 independent variables in the model. The means that independent variables do not hypotheses of t test are: affect on the dependent variable (Gujarati,

  2002). Ho : βi =0 Ha : βi ≠ 0 In addition, to investigate the multi-

  The t test rule states that reject H collinearity problem could be done by if p-value < a or if t < -t a/2 or t > t a/2 where looking at the value of Variance Inflation

  

t a/2 is based on a t distribution with n - p - Factor (VIF). In statistical term, the VIF

  1 degrees of freedom. If the test results quantifies the severity of

  Table 1. Perceived Usefulness toward Organic Farming among Semi and Conventional Farmers Code Measurement Semi Conventional mean SD mean SD PU1 Practicing organic farming 6.31 0.536837 5.963333 0.700207 would improve land fertility PU2 Practicing organic farming would increase the 5.91 0.629726 5.336667 1.137674 productivity

  PU3 Practicing organic farming would enhance the effectiveness on paddy 5.946667 0.641765 5.37 1.232137 cultivation so reducing cost production PU4 Practicing organic farming would make easier in 6.3 0.569574 5.903333 0.659879 preparation of land (tillage)

  PU5 I would find organic farming useful in term increasing 5.94 0.61454 5.25 1.196777 income

  PU6 Practicing organic farming gives me greater control over 5.693333 0.703043 5.09 1.273042 my work in paddy field

  PU7 The price of selling organic rice is very good for me to 5.946667 0.852199

  5.13 1.421208 start practicing organic farming PU8 The advantages of organic farming will outweigh the 5.716667 0.691363 5.053333 1.320214 disadvantages

  PU9 Over all, practicing organic 6.046667 0.582196 5.306667 1.250801 farming will be advantageous

Mean 5.978889 5.378148

  International Conference on Agribusiness Development for Human Welfare 2016

  This result is consonant with the study of Sukristiyonubuwo et al (2011) that revealed the farmer’s reason to convert paddy farming systems from conventional into organic primarily to improve land fertility and facilitate the land preparation.

  in ananalysis. Juanda (2009) revealed that in the regression equation model, if VIF value was less than 10 indicated there was no multicollinearity in the model.

RESULT AND DISCUSSION Farmer’s Perception and Attitudes on Organic Farming

  that using a particular system would enhance his or her productivity ” (Davis,

  1989). The farmer’s perception toward the usefulness of organic farming (PU) is presented in Table 1. Since PU as a latent variable, there are 9 measurement variables of PU in both semi organic and conventional farmer. Based on Table 1 shows that the highest score for semi organic farmer is attained by point 1 (PU1) namely organic farming will improve soil fertility, followed by PU4= easier for preparation of land (tillage) and PU9 = generally will be advantageous.

  Perceived of usefulness is defined as “the degree to which a person believes

  Attitude toward organic farming practices

  Perceived Usefulness

  “the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question

  ” (Azjen, 1991). The attitude of farmers toward organic farming practice is presented in Table 2. In general, the attitude score in both farmer’s type toward organic farming is enough high. Further, there is a similarity between semi and conventional farmer in term of rank of attitude. Farmer place AT1

  Table 2. The Attitude toward Organic Farming among Semi and Conventional Farmers

  

Code Measurement Semi Conventional

mean SD mean SD AT1 Practicing organic farming is a good idea 6.143333 0.50029 5.756667 0.799742 AT2 Practicing organic farming is a wise idea

  6.11 0.587979 5.62 0.926532 AT3 Practicing organic farming is a pleasant idea 5.843333 0.716823 5.293333 1.213341

  AT4 I like the idea of practicing organic farming.

  5.93 0.647945 5.253333 1.254752 AT5 Practicing organic farming will bring profit for me 5.976667 0.646153 5.336667 1.33012 Mean 6.000667 5.452

  Attitude is defined as Ashari, Juwaidah Sharifuddin, Zainal Abidin Mohammed, Rika Terano

  (practicing organic farming is good idea) as the first rank followed by PU2 (organic farming practice as wise idea). They also deem that the organic farming will bring profit for them as the third order. The mean of total measurement score indicates the score of semi organic farmer still is higher than conventional farmer i.e., 6.000667 vs. 5.452.

  Environmental concern

  Environmental concern is “altruism toward other human being, to incorporate both self interest, or egoism, and concern with other species or the biosphere itself”

  (Stern et al 1993). In term of organic farming the aspect of environmental awareness is central issue. The more awareness the higher appreciation toward organic farming practices. Table 3 shows the highest rank for semi organic is EN3 and followed by EN5 and EN4. Semi organic farmer places organic farming benefit everyone, support environmental conservation and protect natural predator as the three best reasons. Meanwhile, conventional farmer proposes EN4, EN1 and EN3 respectively in term their environmental concern expression. There is similarity in EN 3 and EN4 but conventional farmer has own opinion that practicing organic farming will secure their livelihood as farmer (EN1) as a key factor.

  Perceived risk toward organic farming practice

  Perceived risk is “the one’s perception of the uncertainty ad adverse consequence of desired outcome” (Fu et

  al 2006). Farmers' perceptions related to

  the risks that could be emerged if they practice organic farming presented in Table 4. It is indicated that the semi- organic farmers are most concerned about the risk for PR1 which will reduce revenue, followed by PR3 (the risk of production) and then the PR4 (marketing risks). Meanwhile for conventional farmers the highest score is points PR2 that is uncomfortable (anxiety), followed by PR1 (the possibility of reduced income) and PR3 (production risk). Table 4 also indicates the differences in the pattern of perception compared to the previous construct. In term of perceived risk, all of measurements variables score demonstrate that the conventional farmer is always greater than the semi organic farmer. The mean score for all items also approve that perceived risk risk is higher for conventional farmers (2.5200 vs. 3.3200). The study of Prihtanti (2014) in Sragen and Karanganyar also revealed that the level of risk perceived by conventional farmers is greater than

  Table 3. Environmental Awareness toward Organic Farming Code Measurement Semi Conventional mean SD mean SD EN1 Protecting the environment by practicing organic farming will secure my livelihood as farmer 5.94 0.625329 5.556667 0.877128

  EN2 Pollution generated by conventional farming harm people.

  5.906667 0.898506 5.366667 1.096767 EN3 Environmental concern by practicing organic farming benefits everyone.

  6.136667 0.564847 5.503333 1.116907 EN4 Environmental concern by practicing organic farming beneficial to protect natural predator 6.043333 0.607745 5.573333 0.942115

  EN5 I practice organic farming to support environmental conservation task 6.05 0.601698 5.436667 1.090851

Mean 6.015333 5.487333

  International Conference on Agribusiness Development for Human Welfare 2016

  farmers who have practiced organic The Effect of Perception and Attitudes farming system. toward Behavioral Intention

  Behavioral intention to adopt organic

  The result of data analysis

  farming

  presented in Table 6 and 7. Such tables Ajzen (1991) argued that indicate the effect of perception and

  Behavioral Intention (BI) reflects how hard attitude toward behavioral intention in a person is willing to try, and how semi organic farmer and conventional motivated he or she is, to perform the farmer’s cases respectively. Based on behavior. Table 5 shows the intention of

  Table 6 indicates that PU, EN and AT both farmer types to adopt organic influence positively toward behavioral farming. For semi organic farmers, it intention for organic farming adoption. appears that the highest score is the point