Factors Affecting Delivery Performance of Pamarican District Farmers' Unhulled Rice Grain Supply Chain System of Ciamis Regency with PT Mitra Desa Pamarican
DOI:
https://doi.org/10.22219/agriecobis.v5i1.18517Keywords:
Supply Chain, Delivery Performance, PaddyAbstract
One of the problems in fulfilling the staple food consumption of rice in Indonesia is the rice distribution system. Delivery performance is one of the important measurements in the supply chain system since it is an indicator of the accuracy of the quantity and time of grain delivery from rice farmers involved in partnership with PT MDP. Respondents used in this study consisted of 30 rice farmers chosen through purposive sampling technique in Pamarican District, Ciamis Regency, West Java. The analytical method used is multiple linear regression or multiple linear regression model with Ordinary Least Square to analyze the influence of the distance of the farmer to the grain collection point, the length of time the farmer makes inventory, the experience of farming, the farmer's storage capacity, and the method of payment for grain or the transaction system on the delivery performance. The results of the analysis show the variables of distance, inventory, and transaction systems. The distance variable has a significant positive effect, the inventory variable has a significant negative effect, and the cash transaction system will improve the delivery performance of farmers to PT MDP. Farmers make cost efficiency for grain delivery by collecting grain first. A decrease in delivery performance occurs when farmers store the grain longer
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Agustina, Y., Mulyo, J. H., Waluyati, L. R., & Mazwan, M. Z. (2021). Consumer Preferences toward Goat Milk. Agriecobis : Journal of Agricultural Socioeconomics and Business, 4(2), 100–109. https://doi.org/10.22219/agriecobis.v4i2.15922
Ahmad, F., & Khan Sherwani, R. A. (2015). Power comparison of various normality tests. Pakistan Journal of Statistics and Operation Research, 11(3), 331–345. https://doi.org/10.18187/pjsor.v11i3.845
Alim, S. H., Retnoningsih, D., & Koestiono, D. (2018). Kinerja Manajemen Rantai Pasok Keripik Apel Pada Industri Kecil di Kota Batu. HABITAT, 29(1), 38–49. https://doi.org/10.21776/ub.habitat.2018.029.1.5
Arhim, M., Putri, D. A., Nurlaela, N., Rahmaniah, R., Anisa, A., Rukka, M. R., Risamasu, P. I. M., & Kamariah, N. (2019). Supply chain management performance toward competitiveness of chili as main agriculture commodity. IOP Conference Series: Earth and Environmental Science, 343(1), 1–8. https://doi.org/10.1088/1755-1315/343/1/012108
Bidarti, A., Yulius, Y., & Purbiyanti, E. (2021). Design and Planning of The Porang Supply Chain in South Sumatra. Agriecobis : Journal of Agricultural Socioeconomics and Business, 4(2), 133–141. https://doi.org/10.22219/agriecobis.v4i2.17407
Bumblauskas, D., Mann, A., Dugan, B., & Rittmer, J. (2019). A Blockchain Use Case in Food Distribution: Do You Know Where Your Food Has Been? International Journal of Information Management, 52(2020), 1–10. https://doi.org/10.1016/j.ijinfomgt.2019.09.004
Chopra, S., Laux, C., Schmidt, E., & Rajan, P. (2017). Perception of performance indicators in an agri-food supply chain: A case study of India’s Public Distribution System. International Journal on Food System Dynamics, 8(2), 130–145. https://doi.org/10.18461/ijfsd.v8i2.824
Daoud, J. I. (2017). Multicollinearity and Regression Analysis. Journal of Physics: Conference Series, 949(1), 1–6. https://doi.org/10.1088/1742-6596/949/1/012009
Do, T. T. (2017). A Review of The Role of Collectors in Vietnam’s Rice Value Network. 2(2), 85–98. https://doi.org/10.19275/RSEP019
Fadia, R. N., Dwi, R., & Anisa, A. (2019). Risk Mitigation of Sustainable Supply Chain for Food Product Based on Apple Commodity. Russian Journal of Agricultural and Socio-Economic Sciences, 12(96), 60–68. https://doi.org/10.18551/rjoas.2019-12.08
Farmer, J. R., & Betz, M. E. (2016). Rebuilding local foods in Appalachia: Variables affecting distribution methods of West Virginia farms. Journal of Rural Studies, 45(2016), 34–42. https://doi.org/10.1016/j.jrurstud.2016.03.002
Handayani, S., Affandi, M. I., & Irawati, L. (2019). Identifying Supply Chain Performance of Organic Rice in Lampung. International Journal of Applied Business and International Management, 4(2), 49–56. https://doi.org/10.32535/ijabim.v4i2.566
Hartati, M., & Efendi, D. (2016). Analisis Pengukuran Kinerja Aliran Supply Chain di PT. Asia Forestama Raya dengan Metode Supply Chain Operation Reference (SCOR). Prosiding Seminar Nasional XI “Rekayasa Teknologi Industri Dan Informasi 2016 Sekolah Tinggi Teknologi Nasional Yogyakarta, 11(ReTII), 349–356. https://doi.org/10.24014/jti.v3i2.5574
Hidayat, A. P., Yudoko, G., & Pradono, P. (2019). Analisis Kinerja Pengiriman Barang terhadap Pelayanan E-commerce PT Pos Indonesia (Persero). Jurnal Transportasi Multimoda, 17(2019), 14–21.
Hossain, M., & Jahan, R. (2015). Assessing Bangladesh rice supply chain through SCOR modelling frame for planning effective integration of public and private actors. International Journal of Automation and Logistics, 1(4), 320–342. https://doi.org/10.1504/ijal.2015.074311
Hsieh, D. A. (1983). A Heteroscedasticity-Consistent Covariance Matrix Estimator for Time Series Regressions. Journal of Econometrics, 22(3), 281–290. https://doi.org/10.1016/0304-4076(83)90104-5
Hsu, B.-M., Hsu, L.-Y., & Shu, M.-H. (2013). Evaluation of supply chain performance using delivery-time performance analysis chart approach. Journal of Statistics and Management Systems, 16(1), 73–87. https://doi.org/10.1080/09720510.2013.777568
InterCAFE IPB University. (2018). Final Report: Market Study on Food Sector in Indonesia. International Center for Applied Finance and Economics: Lembaga Penelitian Pengembangan Masyarakat (LPPM) IPB, 220. https://kppu.go.id/wp-content/uploads/2019/09/Market_Study_Report_JICA.pdf
Jarque, C. M., & Bera, A. K. (1987). A Test for Normality of Observations and Regression Residuals. International Statistical Review, 55(2), 163–172.
Karo, N. B. (2015). Analisis Optimasi Distribusi Beras Bulog Di Provinsi Jawa Barat. Jurnal OE, 7(3), 252–270. https://doi.org/10.22441/jurnal_mix
Kasimin, S., Desparita, N., & Zakiah, Z. (2021). The Effectiveness of Rice Flow in Large-Scale Rice Refineries in Bireuen Regency. IOP Conference Series: Earth and Environmental Science, 667(2021), 1–7. https://doi.org/10.1088/1755-1315/667/1/012046
Katrutsa, A., & Strijov, V. (2017). Comprehensive study of feature selection methods to solve multicollinearity problem according to evaluation criteria. Expert Systems with Applications, 76(2017), 1–11. https://doi.org/10.1016/j.eswa.2017.01.048
Keco, R., Xhoxhi, O., Skreli, E., & Imami, D. (2019). To contract or not contract: Implications for farmer-buyer trading relation performance. International Journal on Food System Dynamics, 10(2), 151–161. https://doi.org/10.18461/ijfsd.v10i2.09
Lyon, J. D., & Tsai, C. L. (1996). A comparison of tests for heteroscedasticity. Journal of the Royal Statistical Society Series D: The Statistician, 45(3), 337–349. https://doi.org/10.2307/2988471
Mgale, Y. J., & Yunxian, Y. (2020). Marketing Efficiency and Determinants of Marketing Channel Choice by Rice Farmers in Rural Tanzania: Evidence from Mbeya Region, Tanzania. Australian Journal of Agricultural and Resource Economics, 59(2020), 1–21. https://doi.org/10.1111/1467-8489.12380
Moazzam, M., Akhtar, P., Garnevska, E., & Marr, N. E. (2018). Measuring Agri-Food Supply Chain Performance and Risk Through a New Analytical Framework: a Case Study of New Zealand Dairy. Production Planning and Control, 29(15), 1258–1274. https://doi.org/10.1080/09537287.2018.1522847
Mor, R. S., Bhardwaj, A., Singh, S., & Khan, S. A. R. (2021). Modelling the Distribution Performance in Diary Industry: a Predictive Analysis. LogForum: Scientific Journal of Logistic, 17(3), 425–440.
Mutaqin, J. Z., & Sutandi, S. (2020). Pengukuran Kinerja Supply Chain Dengan Pendekatan Metode Scor (Supply Chain Operations Reference) Studi Kasus Di Pt Xyz. Jurnal Logistik Indonesia, 5(1), 13–23. https://doi.org/10.31334/logistik.v5i1.1181
Ngniatedema, T., Chen, L., & Guiffrida, A. L. (2016). A modelling framework for improving supply chain delivery performance. International Journal of Business Performance and Supply Chain Modelling, 8(2), 79–96. https://doi.org/10.1504/IJBPSCM.2016.077163
Nyamah, E. Y., Jiang, Y., Feng, Y., & Enchill, E. (2018). Agri-food Supply Chain Performance: an Empirical Impact of Risk. Management Decision, 55(5), 872–891.
Pamungkassari, A. R., Marimin, M., & Yuliasih, I. (2018). Analisis Kinerja, Nilai Tambah dan Mitigasi Risiko Rantai Pasok Agroindustri Bawang Merah. Jurnal Teknologi Industri Pertanian, 28(1), 61–74. https://doi.org/10.24961/j.tek.ind.pert.2018.28.1.61
Pindyck, R. S., & Rubinfield, D. L. (1991). Econometric Models and Economic Forecasts (Third Edit). NY: McGraw-Hill Inc.
Pratama, A. R., Sudrajat, S., & Harini, R. (2019). Analisis Ketersediaan dan Kebutuhan Beras di Indonesia Tahun 2018. Media Komunikasi Geografi, 20(2), 101–114. https://doi.org/10.23887/mkg.v20i2.19256
Agustina, Y., Mulyo, J. H., Waluyati, L. R., & Mazwan, M. Z. (2021). Consumer Preferences toward Goat Milk. Agriecobis : Journal of Agricultural Socioeconomics and Business, 4(2), 100–109. https://doi.org/10.22219/agriecobis.v4i2.15922
Ahmad, F., & Khan Sherwani, R. A. (2015). Power comparison of various normality tests. Pakistan Journal of Statistics and Operation Research, 11(3), 331–345. https://doi.org/10.18187/pjsor.v11i3.845
Alim, S. H., Retnoningsih, D., & Koestiono, D. (2018). Kinerja Manajemen Rantai Pasok Keripik Apel Pada Industri Kecil di Kota Batu. HABITAT, 29(1), 38–49. https://doi.org/10.21776/ub.habitat.2018.029.1.5
Arhim, M., Putri, D. A., Nurlaela, N., Rahmaniah, R., Anisa, A., Rukka, M. R., Risamasu, P. I. M., & Kamariah, N. (2019). Supply chain management performance toward competitiveness of chili as main agriculture commodity. IOP Conference Series: Earth and Environmental Science, 343(1), 1–8. https://doi.org/10.1088/1755-1315/343/1/012108
Bidarti, A., Yulius, Y., & Purbiyanti, E. (2021). Design and Planning of The Porang Supply Chain in South Sumatra. Agriecobis : Journal of Agricultural Socioeconomics and Business, 4(2), 133–141. https://doi.org/10.22219/agriecobis.v4i2.17407
Bumblauskas, D., Mann, A., Dugan, B., & Rittmer, J. (2019). A Blockchain Use Case in Food Distribution: Do You Know Where Your Food Has Been? International Journal of Information Management, 52(2020), 1–10. https://doi.org/10.1016/j.ijinfomgt.2019.09.004
Chopra, S., Laux, C., Schmidt, E., & Rajan, P. (2017). Perception of performance indicators in an agri-food supply chain: A case study of India’s Public Distribution System. International Journal on Food System Dynamics, 8(2), 130–145. https://doi.org/10.18461/ijfsd.v8i2.824
Daoud, J. I. (2017). Multicollinearity and Regression Analysis. Journal of Physics: Conference Series, 949(1), 1–6. https://doi.org/10.1088/1742-6596/949/1/012009
Do, T. T. (2017). A Review of The Role of Collectors in Vietnam’s Rice Value Network. 2(2), 85–98. https://doi.org/10.19275/RSEP019
Fadia, R. N., Dwi, R., & Anisa, A. (2019). Risk Mitigation of Sustainable Supply Chain for Food Product Based on Apple Commodity. Russian Journal of Agricultural and Socio-Economic Sciences, 12(96), 60–68. https://doi.org/10.18551/rjoas.2019-12.08
Farmer, J. R., & Betz, M. E. (2016). Rebuilding local foods in Appalachia: Variables affecting distribution methods of West Virginia farms. Journal of Rural Studies, 45(2016), 34–42. https://doi.org/10.1016/j.jrurstud.2016.03.002
Handayani, S., Affandi, M. I., & Irawati, L. (2019). Identifying Supply Chain Performance of Organic Rice in Lampung. International Journal of Applied Business and International Management, 4(2), 49–56. https://doi.org/10.32535/ijabim.v4i2.566
Hartati, M., & Efendi, D. (2016). Analisis Pengukuran Kinerja Aliran Supply Chain di PT. Asia Forestama Raya dengan Metode Supply Chain Operation Reference (SCOR). Prosiding Seminar Nasional XI “Rekayasa Teknologi Industri Dan Informasi 2016 Sekolah Tinggi Teknologi Nasional Yogyakarta, 11(ReTII), 349–356. https://doi.org/10.24014/jti.v3i2.5574
Hidayat, A. P., Yudoko, G., & Pradono, P. (2019). Analisis Kinerja Pengiriman Barang terhadap Pelayanan E-commerce PT Pos Indonesia (Persero). Jurnal Transportasi Multimoda, 17(2019), 14–21.
Hossain, M., & Jahan, R. (2015). Assessing Bangladesh rice supply chain through SCOR modelling frame for planning effective integration of public and private actors. International Journal of Automation and Logistics, 1(4), 320–342. https://doi.org/10.1504/ijal.2015.074311
Hsieh, D. A. (1983). A Heteroscedasticity-Consistent Covariance Matrix Estimator for Time Series Regressions. Journal of Econometrics, 22(3), 281–290. https://doi.org/10.1016/0304-4076(83)90104-5
Hsu, B.-M., Hsu, L.-Y., & Shu, M.-H. (2013). Evaluation of supply chain performance using delivery-time performance analysis chart approach. Journal of Statistics and Management Systems, 16(1), 73–87. https://doi.org/10.1080/09720510.2013.777568
InterCAFE IPB University. (2018). Final Report: Market Study on Food Sector in Indonesia. International Center for Applied Finance and Economics: Lembaga Penelitian Pengembangan Masyarakat (LPPM) IPB, 220. https://kppu.go.id/wp-content/uploads/2019/09/Market_Study_Report_JICA.pdf
Jarque, C. M., & Bera, A. K. (1987). A Test for Normality of Observations and Regression Residuals. International Statistical Review, 55(2), 163–172.
Karo, N. B. (2015). Analisis Optimasi Distribusi Beras Bulog Di Provinsi Jawa Barat. Jurnal OE, 7(3), 252–270. https://doi.org/10.22441/jurnal_mix
Kasimin, S., Desparita, N., & Zakiah, Z. (2021). The Effectiveness of Rice Flow in Large-Scale Rice Refineries in Bireuen Regency. IOP Conference Series: Earth and Environmental Science, 667(2021), 1–7. https://doi.org/10.1088/1755-1315/667/1/012046
Katrutsa, A., & Strijov, V. (2017). Comprehensive study of feature selection methods to solve multicollinearity problem according to evaluation criteria. Expert Systems with Applications, 76(2017), 1–11. https://doi.org/10.1016/j.eswa.2017.01.048
Keco, R., Xhoxhi, O., Skreli, E., & Imami, D. (2019). To contract or not contract: Implications for farmer-buyer trading relation performance. International Journal on Food System Dynamics, 10(2), 151–161. https://doi.org/10.18461/ijfsd.v10i2.09
Lyon, J. D., & Tsai, C. L. (1996). A comparison of tests for heteroscedasticity. Journal of the Royal Statistical Society Series D: The Statistician, 45(3), 337–349. https://doi.org/10.2307/2988471
Mgale, Y. J., & Yunxian, Y. (2020). Marketing Efficiency and Determinants of Marketing Channel Choice by Rice Farmers in Rural Tanzania: Evidence from Mbeya Region, Tanzania. Australian Journal of Agricultural and Resource Economics, 59(2020), 1–21. https://doi.org/10.1111/1467-8489.12380
Moazzam, M., Akhtar, P., Garnevska, E., & Marr, N. E. (2018). Measuring Agri-Food Supply Chain Performance and Risk Through a New Analytical Framework: a Case Study of New Zealand Dairy. Production Planning and Control, 29(15), 1258–1274. https://doi.org/10.1080/09537287.2018.1522847
Mor, R. S., Bhardwaj, A., Singh, S., & Khan, S. A. R. (2021). Modelling the Distribution Performance in Diary Industry: a Predictive Analysis. LogForum: Scientific Journal of Logistic, 17(3), 425–440.
Mutaqin, J. Z., & Sutandi, S. (2020). Pengukuran Kinerja Supply Chain Dengan Pendekatan Metode Scor (Supply Chain Operations Reference) Studi Kasus Di Pt Xyz. Jurnal Logistik Indonesia, 5(1), 13–23. https://doi.org/10.31334/logistik.v5i1.1181
Ngniatedema, T., Chen, L., & Guiffrida, A. L. (2016). A modelling framework for improving supply chain delivery performance. International Journal of Business Performance and Supply Chain Modelling, 8(2), 79–96. https://doi.org/10.1504/IJBPSCM.2016.077163
Nyamah, E. Y., Jiang, Y., Feng, Y., & Enchill, E. (2018). Agri-food Supply Chain Performance: an Empirical Impact of Risk. Management Decision, 55(5), 872–891.
Pamungkassari, A. R., Marimin, M., & Yuliasih, I. (2018). Analisis Kinerja, Nilai Tambah dan Mitigasi Risiko Rantai Pasok Agroindustri Bawang Merah. Jurnal Teknologi Industri Pertanian, 28(1), 61–74. https://doi.org/10.24961/j.tek.ind.pert.2018.28.1.61
Pindyck, R. S., & Rubinfield, D. L. (1991). Econometric Models and Economic Forecasts (Third Edit). NY: McGraw-Hill Inc.
Pratama, A. R., Sudrajat, S., & Harini, R. (2019). Analisis Ketersediaan dan Kebutuhan Beras di Indonesia Tahun 2018. Media Komunikasi Geografi, 20(2), 101–114. https://doi.org/10.23887/mkg.v20i2.19256
Putri, A. D., Murniati, K., & Nugraha, A. (2020). Analisis Pola Rantai Pasok dan Kinerja Rantai Pasok Agroindustri Kelanting di Kabupaten Pesawaran dan Kabupaten Pringsewu (Studi Kasus Agroindustri Kelanting Darwiyanto dan Agroindustri Kelanting Robbani). Journal of Food System and Agribusiness, 4(1), 1–8. https://doi.org/10.25181/jofsa.v4i1.1563
Rao, M., Rao, P., & Muniswamy, V. V. (2011). Delivery Performance Measurement in an Integrated Supply Chain Management: Case Study in Batteries Manufacturing Firm. Serbian Journal of Management, 6(2), 205–220. https://doi.org/10.5937/sjm1102205m
Santosa, S. P., & Sudrajat. (2017). Kajian Ketersediaan Dan Kebutuhan Konsumsi Beras Di Kabupaten Karanganyar, Jawa Tengah. Jurnal Bumi Indonesia, 6(4), 1–11. https://media.neliti.com/media/publications/228856-kajian-ketersediaan-dan-kebutuhan-konsum-b6cb01ab.pdf
Sharma, V., Giri, S., & Shankar Rai, S. (2013). Supply Chain Management Of Rice In India: A Rice Processing Company’s Perspective. International Journal of Managing Value and Supply Chains, 4(1), 25–36. https://doi.org/10.5121/ijmvsc.2013.4103
Syaifullah, Y. (2013). Ketahanan Pangan dan Pola Distribusi Beras di Propinsi Jawa Timur. JEJAK: Journal of Economics and Policy, 6(2), 103–213. https://doi.org/10.15294/jejak.v7i2.3892
Thompson, C. G., Kim, R. S., Aloe, A. M., & Becker, B. J. (2017). Extracting the Variance In flation Factor and Other Multicollinearity Diagnostics from Typical Regression Results. Basic and Applied Social Psychology, 39(2), 81–90. https://doi.org/10.1080/01973533.2016.1277529
Violenta, D. V., Marwanti, S., & Qonita, R. A. (2019). Analisis Manajemen Persediaan Ikan Segar di Depo Ikan Segar Kota Surakarta. Agriecobis : Journal of Agricultural Socioeconomics and Business, 2(2), 118–133. https://doi.org/10.22219/agriecobis.vol2.no2.118-133
Yap, B. W., & Sim, C. H. (2011). Comparisons of various types of normality tests. Journal of Statistical Computation and Simulation, 81(12), 2141–2155. https://doi.org/10.1080/00949655.2010.520163
Zhafirah, N., Relawati, R., & Ariadi, B. Y. (2021). Service Quality, Product Quality, and Perception of Price for Consumer Satisfaction at Aqiqah Business. Agriecobis : Journal of Agricultural Socioeconomics and Business, 4(2), 142–153. https://doi.org/10.22219/agriecobis.v4i2.17909
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