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ANALISIS PRIORITAS STRATEGI PENGEMBANGAN KAWASAN PERTANIAN PADI BERBASIS PREFERENSI PETANI DI KABUPATEN KENDAL

*Pujiati Sri Rejeki  -  Sekretariat Daerah Kabupaten Kendal, Indonesia
Fadjar Hari Mardiansjah scopus  -  Departemen Perencanaan Wilayah dan Kota, Universitas Diponegoro, Indonesia

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Abstract
Kabupaten Kendal merupakan daerah yang sebagian besar wilayahnya digunakan sebagai lahan pertanian tanaman pangan khususnya komoditas padi. Tujuan dari penelitian ini adalah untuk merumuskan prioritas alternatif strategi pengembangan kawasan pertanian padi utama berdasarkan preferensi petani di Kabupaten Kendal. Pengolahan data dilakukan melalui analisis spasial Kernel Density, analisis spasial interpolasi metode invers distance weighted (IDW), analisis data kualitatif dan analisis pengambilan keputusan prioritas strategi menurut preferensi petani dengan metode analitycal hierarchy process (AHP). Hasil analisis spasial Kernel Density dan interpolasi metode IDW menunjukkan bahwa yang menjadi kawasan pertanian padi utama adalah 134 wilayah desa yang berada di bagian utara wilayah Kabupaten Kendal. Prioritas strategi pengembangan kawasan pertanian padi utama menurut preferensi petani adalah strategi penyediaan sarana dan prasana produksi pertanian sebagai prioritas strategi pengembangan kawasan tersebut. Selanjutnya secara berturut-turut adalah strategi penyediaan infrastruktur pertanian, strategi implementasi regulasi perlindungan lahan pertanian pangan, strategi penguatan kelembagaan petani, strategi peningkatan nilai tambah dan daya saing agribisnis dan terakhir adalah strategi pemberian insentif bagi petani. Pola pengembangan kawasan pertanian padi utama melalui pengembangan kegiatan pertanian on-farm sebagai prioritas pertama dan pengembangan kegiatan pertanian off-farm sebagai prioritas kedua.
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Keywords: strategi pengembangan; kawasan pertanian; preferensi petani

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  1. Boratyńska, K., & Huseynov, R. T. 2016. An innovative approach to food security policy in developing countries. Journal of Innovation & Knowledge, 2, 6–11. https://doi.org/10.1016/j.jik.2016.01.007
  2. Boryan, C. G., Yang, Z., Willis, P., & Di, L. 2017. Developing Crop Specific Area Frame Stratifications Based on Geospatial Crop Frequency and Cultivation Data Layers. Journal of Integrative Agriculture, 16(2), 312–323. https://doi.org/10.1016/S2095-3119(16)61396-5
  3. BPS Kabupaten Kendal. 2016. Kabupaten Kendal Dalam Angka 2016. Kendal
  4. Chen, Y., Song, X., Wang, S., Huang, J., & Mansaray, L. R. 2016. Impacts of Spatial Heterogeneity on Crop Area Mapping in Canada Using MODIS Data. ISPRS Journal of Photogrammetry and Remote Sensing, 119, 451–461. https://doi.org/10.1016/j.isprsjprs.2016.07.007
  5. Devatha, C., & Kumar Thalla, A. 2017. Prioritizing Cropping Alternatives Based on Attribute Specification and Comparison Using MADM Models. Journal of the Saudi Society of Agricultural Sciences. https://doi.org/10.1016/j.jssas.2017.09.007
  6. Dolinska, A. 2017. Bringing Farmers into the Game. Strengthening Farmers’ Role in the Innovation Process through a Simulation Game, A Case from Tunisia. Agricultural Systems, 157(June 2016), 129–139. https://doi.org/10.1016/j.agsy.2017.07.002
  7. Frimawaty, E., Basukriadi, A., Syamsu, J. A., & Soesilo, T. E. B. 2013. Sustainability of Rice Farming based on Eco-Farming to Face Food Security and Climate Change: Case Study in Jambi Province, Indonesia. Procedia Environmental Sciences, 17, 53–59. https://doi.org/10.1016/j.proenv.2013.02.011
  8. Islam, S., Cenacchi, N., Sulser, T. B., Gbegbelegbe, S., Hareau, G., Kleinwechter, U., … Wiebe, K. 2016. Structural approaches to modeling the impact of climate change and adaptation technologies on crop yields and food security. Global Food Security, 10, 63–70. https://doi.org/10.1016/j.gfs.2016.08.003
  9. Jabbar, M. A., Swallow, B. M., & Rege, E. 1999. Incorporation of Farmer Knowledge and Preferences in Designing Breeding Policy and Conservation Strategy for Domestic Animals. Outlook on Agriculture, 28(4), 239–243
  10. Josephson, A. L., Ricker-Gilbert, J., & Florax, R. J. G. M. 2014. How does population density influence agricultural intensification and productivity? Evidence from Ethiopia. Food Policy, 48, 142–152. https://doi.org/10.1016/j.foodpol.2014.03.004
  11. Khatri-Chhetri, A., Aggarwal, P. K., Joshi, P. K., & Vyas, S. 2017. Farmers’ prioritization of climate-smart agriculture (CSA) technologies. Agricultural Systems, 151, 184–191. https://doi.org/10.1016/j.agsy.2016.10.005
  12. Kosolapova, N. A., Matveeva, L. G., Nikitaeva, A. Y., & Molapisi, L. 2017. Modeling Resource Basis For Social And Economic Development Strategies: Water Resource Case. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2017.08.007
  13. Li, H., & Zhang, X. 2017. A Spatial Explicit Assessment of Food Security in Africa Based on Simulated Crop Production and Distribution. Journal of Cleaner Production, 147, 628–636. https://doi.org/10.1016/j.jclepro.2017.01.124
  14. Methorst, R., Roep, D., Verhees, F., & Verstegen, J. 2016. Drivers for differences in dairy farmers perceptions of farm development strategies in an area with nature and landscape as protected public goods. Local Economy, 31(5), 554–571. https://doi.org/10.1177/0269094216655520
  15. Mwalusepo, S., Muli, E., Faki, A., & Raina, S. 2017. Land use and land cover data changes in Indian Ocean Islands: Case study of Unguja in Zanzibar Island. Data in Brief, 11, 117–121. https://doi.org/10.1016/j.dib.2017.01.010
  16. Nahayo, A., Omondi, M. O., ZHANG, X. hui, LI, L. qing, PAN, G. xing, & Joseph, S. 2017. Factors Influencing Farmers’ Participation in Crop Intensification Program in Rwanda. Journal of Integrative Agriculture, 16(6), 1406–1416. https://doi.org/10.1016/S2095-3119(16)61555-1
  17. Pribadi, D. O., & Pauleit, S. 2015. The Dynamics of Peri-Urban Agriculture During Rapid Urbanization of Jabodetabek Metropolitan Area. Land Use Policy, 48, 13–24. https://doi.org/10.1016/j.landusepol.2015.05.009
  18. Shirsath, P. B., Aggarwal, P. K., Thornton, P. K., & Dunnett, A. 2016. Prioritizing climate-smart agricultural land use options at a regional scale. Agricultural Systems, 151, 174–183. https://doi.org/10.1016/j.agsy.2016.09.018
  19. Wang, X., Huang, J., & Rozelle, S. 2017. Off-farm employment and agricultural specialization in China. China Economic Review, 42, 155–165. https://doi.org/10.1016/j.chieco.2016.09.004
  20. Woods, B. A., Nielsen, H. O., Pedersen, A. B., & Kristofersson, D. 2017. Farmer’s Perceptions of Climate Change and Their Likely Responses in Danish Agriculture. Land Use Policy, 65(May 2015), 109–120. https://doi.org/10.1016/j.landusepol.2017.04.007

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