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Production Risk of Rice in Kebonsari, Madiun Regency

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Production Risk of Rice in Kebonsari, Madiun Regency AgroAGRO Ekonomi EKONOMI, Vol. 29/Issue. Vol 29, 2,Issue December 2, December 2018 2018, Page.161-172161 DOI : http://doi.org/10.22146/ae.35711 ISSN 0215-8787 (print), ISSN 2541-1616 (online) Available at https://jurnal.ugm.ac.id/jae/ PRODUCTION RISK OF RICE IN KEBONSARI, MADIUN REGENCY Risiko Produksi Padi di Kebonsari, Kabupaten Madiun Rosita Dewati1, Lestari Rahayu Waluyati2 1Master Student of Agricultural Economics, Faculty of Agriculture, Universitas Gadjah Mada. 2Faculty of Agriculture, Universitas Gadjah Mada. Jl. Flora No. 1 Bulaksumur, Yogyakarta [email protected] Submitted: 22 May 2018; Revised: 10 August 2018; Accepted: 21 September 2018 ABSTRACT This study aims to determine the risks, factors affecting risk and investigate the attitude toward risk in Kebonsari, Madiun regency. This research used primary and secondary data. Primary data obtained purposively by 61 respondents. Coeffi cient of variation (CV) method was used to analyze the risk, while Just and Pope model was used to analyze the factors affecting production risk. Attitude toward risk was analyzed with Moscardi and de Javnry model. The result of production risk analysis shows that production of rice farming in Kebonsari Madiun regency has a low variation which is about 14,80%. It means that production risk faced by paddy farmers in this area is low. Phonska fertilizer and other fertilizer are risk-increasing variables whereas liquid pesticide is risk decreasing variable. The result of K (s) indicated that 91,60% or 56 paddy farmers are risk averter. About 4,92% of paddy farmers are risk lover and 3,28% are risk neutral. The farmers are behaving in rational manner which avoid the possible risk that might be higher than the revenues to be earned. Keywords: attitude toward risk, paddy rice, risk Dewati, R., &Waluyati, L. R. (2018). Production Risk of Rice in Kebonsari, Madiun Regency. Agro Ekonomi, 29(2) : 161-172. INTISARI Penelitian ini bertujuan untuk mengetahui risiko dan faktor-faktor yang mempengaruhi risiko serta mengetahui perilaku petani terhadap risiko produksi padi di Kecamatan Kebonsari Kabupaten Madiun. Data yang digunakan adalah data primer dan data sekunder. Data primer diperoleh secara sengaja dengan sampel sebanyak 61 responden. Metode yang digunakan untuk menganalisis risiko adalah dengan menghitung nilai koefi sien variasi (KV), untuk faktor-faktor yang mempengaruhi risiko produksi digunakan model Just and Pope. Analisis perilaku petani terhadap risiko dengan menggunakan metode Moscardi dan de Javnry. Hasil analisis risiko produksi menunjukkan bahwa produksi usahatani padi di Kecamatan Kebonsari Kabupaten Madiun memiliki variasi yang rendah yaitu sebesar 14,80%. Artinya risiko produksi yang dihadapi petani padi di lokasi penelitian rendah. 162 Agro Ekonomi Vol. 29/Issue. 2, December 2018 Variabel pupuk phonska dan pupuk lain merupakan variabel yang meningkatkan risiko (risk-increasing) sedangkan variabel pestisida cair merupakan variabel yang menurunkan risiko (risk-decreasing). Hasil penghitungan nilai K(s) menunjukkan bahwa 91,60% petani padi cenderung bersikap enggan terhadap risiko produksi (risk averter). Sebesar 4,92% bersikap menyukai risiko dan 3,28% netral terhadap risiko. Petani bersikap rasional yaitu menghindari risiko yang mungkin lebih tinggi dari pendapatan yang akan diperoleh. Kata Kunci: Padi, Perilaku terhadap risiko, Risiko INTRODUCTION Madiun Regency in 2016 was increasing Rice is considered as one of the most from 543,378.55 ton to 596,135.1 ton consumed staple food worldwide. Thus, it is (Badan Pusat Statistik Kabupaten Madiun, not surprising that rice has always become 2017). However, in the last two years, rice the prioritized commodity to be developed productivity has declined, even in the time in agricultural sector. The demand of rice is of sharp improvements were occurred on increasing signifi cantly due to the growing its production and harvesting area. The number of population. In Indonesia, the declining productivity can be a sign of annual consumption rate of rice is 124.89 kg ineffi cient farming. Thus, the yield is not per capita. On the other hand, the number of optimal. Futhermore, there are possibilities Indonesians has reached 255.46 million with that the existing risk in farming was not 1.31% rate of population growth showing considered by farmers. Production risk that this escalation could affect supply can be caused by external and internal and demand of rice (Pusdatin Kementrian factors. In this study, it focuses on internal Pertanian, 2016). East Java is one of the rice factors, by including input factors of rice granaries in Indonesia. About 33.75% of total farming. Moreover, the effect of inputs on rice producer in Java Island comes from this the production risk can be identifi ed. province. It indicates that East Java has a Farmer’s attitude towards risk plays pivotal role in supplying it within national a major role in rice farming. Nainggolan level. et al., (2017) states that it would determine To be more specific, Madiun is farmer’s decision in allocating the input one of paddy producers in East Java. Its that will infl uence the technical effi ciency paddy harvesting area continued to rise, rate achieved by farmer. Thus, it will affect and experienced a sharp improvement in the level of rice productivity. Futhermore, the last 2 years from 85,741 ha in 2015 Abdullah et al., ( 2015) states that it also to 95,432 ha in 2016. This escalation generates an impact for each decision also occurred in the quantity of paddy made by farmers in their farming business. production. The paddy production in While the decision in production activities Agro Ekonomi Vol. 29/Issue. 2, December 2018 163 is characterized by the uncertainty or the de Javnry method to determine farmer’s unavailability of information or complete attitude towards risk. The expected result knowledge, farmers usually take a current- is that all input factors can increase rice time decision which will determine their production. Labor and seeds are variables output or yield in the future. Farmers have that are expected to reduce risk. Other to deal with the changes in several factors variables such as land area, all fertilizers such as weather, government policies, and and pesticides can increase risk. Increasing technology which will put them in diffi culty fertilizer to a certain point will have a good to forecast the future of their agricultural impact on plants, further use of fertilizer situation. Referring to the importance of will reduce the quality of crops. The use of understanding farmer’s attitude towards pesticides has a negative impact on human production risk, this research aims to health and the environment (Guttormsen & discover the factors affecting production Roll, 2013). In addition, all the farmers are risk of rice and the farmers’ attitude expected to averse the risk. towards the risk in Kebonsari District of Madiun Regency. This research is focused METHODS on farmers’ land with technical irrigation Location and Data and artesian well. It is due to the limited Location selection in this research discharge of irrigation water in the study was performed purposively. Kebonsari area that irrigation line has not been able District was selected because this district to fulfi l the crop’s needs. is the third largest producer of paddy in Based on previous study, such as Madiun Regency and Kebonsari District is Suharyanto et al., (2015) used the coeffi cient one of the four districts with the condition of variation (CV) and Just and Pope models of paddy fi elds that already have technical to analyze the risk of rice production. irrigation line with largest harvesting area. Meanwhile, Guttormsen & Roll (2013) This research used primary data that used multiple linear regression analysis was acquired through interview towards with heteroscedasticity multiplicative paddy farmers in Kebonsari District. The method (Just and Pope) and Yang et al., sample farmers were selected purposively (2016) used stochastic frontier to analyze which result in 61 respondents as the ineffi ciency and the marginal production paddy farmers in Rejosari and Tambak risk to analyze risk. This study used three Mas Villages of Kebonsari District. The methods consisting of (1) Coefficients collected data was the data of one plantation of Variation and (2) Just and Pope to season of 2017. The secondary data was analyze risk and (3) the Moscardy and acquired from various related institutions. 164 Agro Ekonomi Vol. 29/Issue. 2, December 2018 Method of Analysis Ln y = Ln α0 + α1 Ln X1 + α2 Ln X2 + α3 This research was analyzing the Ln X3 + α4 Ln X4 + α5 Ln X5 + α6 Ln X6 + production risk, the factors that determine α7 Ln X7 + α8 Ln X8 + α9 Ln X9 + α10 Ln the production risk and the farmer attitude X10 + εi 2 towards the production risk of paddy in (ε1 ) = Ln β0 + β1 Ln X1 + β 2 Ln X2 + β3 Kebonsari District of Madiun Regency. Ln X3 + β4 Ln X4 + β5 Ln X5 + β6 Ln X6 + β7 Ln X7 + β8 Ln X8 + β9 Ln X9 + β10 Ln X10 Risk Analysis +ε2 The number of risk value of rice Notes : production in this research was measured y : yield (kg) 2 through CV value. Coeffi cient of variation ε1 : production risk is the size of relative risk by dividing X1 : land area (ha) the deviation standard with the expected X2 : seed (kg) average value. The value of coeffi cient of X3 : urea fertilizer (kg) variation (CV) can be written systematically X4 : ZA fertilizer (kg) as follows: X5 : phonska fertilizer(kg) X6 : organic fertilizer (kg) X7 : another fertilizer (kg) X8 : liquid pesticide (litre) X9 : solid fertilizer (kg) Notes : X10 : labors (HOK) CV : coeffi cient of variations α0, β0 : intercept : standar deviation of yield αi , βi : parameter coeffi cients, i = 1, 2, 3, X : yield of rice (kg/ha) ..., 10 : average of yield (kg/ha) ε1, ε2 : error term n : total of sample The estimated regression coeffi cient value The amount of influence of - β1-β9 < 0 production factor utilization towards risk Hypotheses Tests: can be analyzed by using the multiple linear H0 : βi = 0 , input-i has generated no regression model of heteroscedasticity infl uence towards the production risk method by Just and Pope (Just & Pope, H1 : βi ≠ 0 , input-i has generated an 1979).
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