Determinant Variable of Net income of Two Cobs Hybrid Corn Farm: Panel Data Analysis of Three Districts in South Sulawesi, Indonesia

Muhammad Basir Paly

Abstract


Abstract

This study aimed to analyze the net income variables of 2 cobs hybrid corn farm using panel data. The study was implemented in three districts of corn production center of 2 cobs hybrids corn in South Sulawesi. Using survey method on 75 farm samples with three period of times (2015-2017). Observations were made on each sample with two cropping indexes, so that the total observation data was 450. There were 19 variables observed; total area of farming (X1); soil processing (X2), productivity (X3), seed price (X6), fertilizer price (X7), pesticide price (X8), labor cost (X9), cost of living (X10), post-harvest cost (X11), irrigation cost (X12), equipment and machine maintenance cost (X13) and depreciation cost (X14). The data were analyzed by harvest data regression using Eviews 7. The analysis showed the determinant (R2) 0.563. That was, 56.30% net income was determined by 14 variables, while the remaining 43.70% was determined by other variables not included in the model. Out of the 14 variables, there were 9 significant variables (p <0.05) and can be categorized as determinant variable. That was; X1, X3, X4, X5, X9, X10, X11, X12 and X14. While 5 not-significant variables (p> 0.05) were categorized as not-determinant; the X2, X6, X7, X8, and X13.  These 5 variables directly affect the productivity, not the net income. Without ignoring the 5 not-determinant variables, it is suggested that farmers should prioritize the 9 determinant variables in the increase of net income 2 cobs hybrid corn farm.

Key word: deciding variablet, longitudinal data, net earning, hybrid maize, two cobs

Keywords


Key word: deciding variablet, longitudinal data, net earning, hybrid maize, two cobs

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References

CADIS (Center for Agricultural Data and Information System). 2017. Agricultural Statistics 2017. Ministry of Agriculture Republic of Indonesiac Jakarta, Indonesia. Available onlinre: http://epublikasi.setjen.pertanian.go.id/download/file/390-statistik-pertanian-2017 (accessed on 12 March 2018), ISBN : 979-8958-65-9.

Nuryati L, Waryanto B, Akbar, Widaningsih R. 2016. Outlook Komoditas Pertanian Tanaman Pangan, Jagung. Jakarta, Pusat Data dan Sistem Informasi Pertanian Kementerian Pertanian. ISBN : 1907 –1507

Yorobe J.M.J, Smale M. 2012. Impacts of Bt Maize on Smallholder Income in the Philippines. AgBioForum, 15:152-16.

Mathenge M.K, Smale M, Olwande J. 2014. The impacts of hybrid maize seed on the welfare of farming households in Kenya. Food Policy, 44:262–271. https://doi.org/10.1016/j.foodpol.2013.09.013

Otunaiya A.O, Ologbon O.A.C and Oyebanjo O. 2013.Determinants of Financial Performance of Maize Farms in Egba Division of Ogun State, Nigeria. IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS), 4: 27-30. www.iosrjournals.org

Banerjee H, Goswami R, Chakraborty S, Dutta S, Majumdar K, Satyanarayana T, Jat M.L, Zingor S. 2014. Understanding biophysical and socio-economic determinants of maize (Zea maysL.) yield variability in eastern India. NJAS-Wageningen Journal of Life Sciences, 70:79–93. https://doi.org/10.1016/j.njas.2014.08.001. www.elsevier.com/locate/njas

Miladis M, Afidchao, Musters C.J.M, Wossink A,.Balderama O.F, de Snoo G.R. 2014. Analysing the farm level economic impact of GM corn in the Philippines. NJAS - Wageningen Journal of Life Sciences, 70:113–121 . https://doi.org/10.1016/j.njas.2014.05.008

Zalkuwi J, Ibrahim A, Kwakanapwa E. 2014. Analysis of Cost and Return of Maize Production in Numan Local Government Area of Adamawa State, Nigeria. International journal of innovative research, 3:62-68. www.ijird.com

Dhakal S.C, Regmi P.P, Thapa R.B, Kumar S.S, Khatri-Chhetri D.B. 2015. Productivity and profitability of maize-pumpkin mix cropping in Chitwan, Nepal. Journal of Maize Research and Development,1:112-122. DOI: http://dx.doi.org/10.5281/zenodo.34290.

Koondhar M, HeGe, Chandio A, Abbas, Xaio X, Koondhar A.M. 2016. Economic Analysis of Hybrid Maize Cultivation in Distt. Journal of Poverty, Investment and Developmen, 18:56-62. Available online: https://www.researchgate.net/publication/289389535_Economic_Analysis_of_HybridMaize_Cultivation_in_Distt (accessed on 12 Juni 2017).

Garba Y, Ahmed B,Katung M.D, Lawal A.F, Abubakar H.N. 2017. Profitability of striga tolerant maize variety (SAMMAZ 17) amongst smallholder farmers in Lapai, Niger State, Nigeria. S Afr. Jnl. Agric. Ext., 45:1-9. http://dx.doi.org/10.17159/2413-3221/2017/v45n1a400.

Surhano and Rusdi, 2017.Kelayakan Usahatani Jagung Hibrida di Kabupaten Muna, Provinsi Sulawesi Tenggara. Jurnal Pengkajian dan Pengembangan Teknologi Pertanian, 20:36-46. Availabe online: http://www.bbp2tp.litbang.pertanian.go.id (accessed on 12 December 2017). b/c rasio hibrida lebih tinggi (1.7) dan local (1.5)

Wang Y, Vitale J, Park P, Adams B, Agesa B and Korir M. 2017.Socioeconomic determinants of hybrid maize adoption in Kenya. African Journal of Agricultural Research, 12: 617-631. DOI: https://doi.org/10.5897/AJAR2016.11958. http://www.academicjournals.org/AJAR

Baylis, K., Paulson, N., & Piras, G. 2011. Spatial Approaches to Panel Data in Agricultural Economics: A Climate Change Application. Journal of Agricultural and Applied Economics, 43:325-338. doi:10.1017/S1074070800004326.

Platoni, Sckokai P, Moro D; Panel. 2012. Data Estimation Techniques and Farm-level Data Models. American Journal of Agricultural Economics, 94:1202–1217, https://doi.org/10.1093/ajae/aas072

Olatunji T.A and Matthew I.E. 2016. Food Production Modelling Using Fixed Effect Panel Data for Nigeria and Other 14 West African Countries (1990-2013). American Journal of Theoretical and Applied Statistics, 5: 208-218. doi: 10.11648/j.ajtas.20160504.17

Gujarati D.N, Porter D.C. 2011. Dasar-Dasar Ekonometrika (Book 2), (5-ed). Salemba Empat, Jakarta. ISBN 9789790610668.

Ekanandan M. 2014. Analisis Ekonometrika Data Panel. Jakarta-Indonesia: Mitra Wacana Media. ISBN 978-602-1353-99-8

Widarjono A. 2016. Ekonometrika; Pengantar dan Aplikasi Disertai Panduan Eviews, Yogyakarta-Indonesia: UPT STIM YKPN. ISBN 978-979-5332-10-1

Arsyad Biba, M. (2016).Preferensi Petani terhadap Jagung Hibrida Berdasarkan Karakter Agronomik, Produktivitas, dan Keuntungan Usahatani. Jurnal Penelitian Pertanian Tanaman Pangan, 35:81-88. DOI:10.21082/jpptp.v35n1.2016.p81-88.

Taufik M, Maintang, and Nappu M.B. 2015. Feasibility Analysis of Maize Farming System in South Sulawesi Province. Jurnal Pengkajian dan Pengembangan Teknologi Pertanian Vol. 18, No.1, Maret 2015 : 67-80.DOI: http://dx.doi.org/10.21082/jpptp.v18n1.2015.p%25p.Website : http://www.bbp2tp.litbang.pertanian.go.id

Subagyo, 2018.Balitbang Pertanian lepas 39 varietas jagung hibrida. Available online: https://www.antaranews.com/berita/686489/balitbang-pertanian-lepas-39-varietas-jagung-hibrida (accessed on 3 March 2018).

Ntabakirabose G, Mbabazize M, Shukla J. 2015. An Analytical Study of the Factors Influencing Maize Production in Rwanda: A Case Study of Gatsibo District. The International Journal Of Business & Management, 3:146-181. www.theijbm.com. Available online: http://www.theijbm.com/force_download.php?file_path=wp-content/uploads/2015/10/16.-BM1509-054.pdf&id=1995 (accessed on 20 Mey 2017).

Gittinger J. P. 2008. Analisa ekonomi proyek-proyek pertanian (Economic analysis of agriculture project). Jakarta, Universitas Indonesian (UI-Press), ISBN: 9798034287 9789798034282 1986 ,

Bidzakin J.K, Fialor S.C, and Asuming-Brempong D. 2014. Small Scale Maize Production In Northern Ghana: Stochastic Profit Frontier Analysis. ARPN Journal of Agricultural and Biological Science, 9: 76-83. www.arpnjournals.com

Sudjana. 2005. Metoda Statistika. Tarsito, Bandung. ISBN 9799185378.

Mbamalu M.B.Y and Yigezu T.T. 2016. Determination of Optimal Irrigation Scheduling for Maize (Zea Mays) at Teppi, Southwest of Ethiopia. Irrigat Drainage Sys Eng 5:173. doi: 10.4172/2168-9768.1000173

Harendra P.S.C, Singh G.P, Singh R, Kushwaha P, Kumar R and Ranjan A.K. 2018. Costs and Income Analysis of Maize Cultivation in Bahraich District of Uttar Pradesh.Int.J.Curr.Microbiol.App.Sci. 7(2): 1060-1065. doi: https://doi.org/10.20546/ijcmas.2018.702.131n

Abass A.B, Ndunguru G, Mamiro P, Alenkhe B, Mlingi N, Bekunda M. 2014. Post-harvest food losses in a maize-based farming system of semi-arid savannah area of Tanzania. Journal of Stored Products Research, 57: 49-57. https://doi.org/10.1016/j.jspr.2013.12.004. ournal homepage: www.elsevier.com/locate/jsp.

Kozlovska I. 2015.The impact of long-lived non-financial assets depreciation/ amortization method on financial statements. Copernican Journal of Finance & Accounting, 4:91–108. http://dx.doi.org/10.12775/CJFA.2015.018

Mafongoya P, Obert J, Phophi M. 2016. Evaluation of Tillage Practices for Maize (Zea mays) Grown on Different Land-Use Systems in Eastern Zambia.Sustainable Agriculture Research. 5:10-23. doi:10.5539/sar.v5n1p10 URL: http://dx.doi.org/10.5539/sar.v5n1p10.

Esham M. 2014. Technical Efficiency and Determinants of Maize Production by Smallholder Farmers in the Moneragala District of Sri Lanka. Mediterranean Journal of Social Sciences, 5:416-422. Doi:10.5901/mjss.2014.v5n27p416.

Ibrahim K, Shamsudin M.N, Yacob R and Radam A.B. 2014. Technical Efficiency in Maize Production and its Determinants: A Survey of Farms Across Agro Ecological Zones in Northern Nigeria. Trends in Agricultural Economics, 7: 57-68. DOI:10.3923/tae.2014.57.68URL:https://scialert.net/abstract/?doi=tae.2014.57.68

Soenartiningsih S. 2015. Uji Ketahanan beberapa Varietas Unggul Jagung terhadap Penyakit Gibberella dan Diplodia. Biosfera 32 :103 – 109. Available online: https://journal.bio.unsoed.ac.id/index.php/biosfera/article/view/301 (accessed on 20 April, 2016).

Daryono B.S, Purnomo, Parazulfa A. 2017. Uji Ketahanan Tujuh Kultivar Jagung (Zea mays L.) Terhadap Penyakit Bulai (Peronosclerospora spp.). Biogenesis, 6: 11-17. DOI https://doi.org/10.24252/bio.v6i1.4175. 7

Bonhee C, Arshad F.M, Kusairi M.N, Sidique S.F. 2016. Cost analysis of rice milling: a case study of 7 rice mills in Malaysia. Journal of Agribusiness in Developing and Emerging Economies, 6: 173-190, https://doi.org/10.1108/JADEE-05-2014-0019.


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