Mapping spatial drivers of rice productivity: A case study of Inpari 36 and 37 in West Java with BYM2-INLA
DOI:
https://doi.org/10.58524/jgsa.v1i2.36Keywords:
BYM2, Inpari 36, Inpari 37, Rice productivity, Spatial modelingAbstract
West Java is one of Indonesia’s largest rice-producing provinces. However, rice production has declined by 23.07% since 2018 due to land conversion. Therefore, this study investigates the factors influencing rice productivity by modeling and mapping the productivity of Inpari 36 and Inpari 37 rice varieties using the Besag York Mollié 2 (BYM2) spatial model with Integrated Nested Laplace Approximation (INLA) inference. The response variable was rice productivity in 27 districts/cities in West Java, with explanatory variables including plant-disrupting organisms, pest-resistant organisms, altitude, average temperature, number of village unit cooperatives, number of tillers, and plant height. The results indicated significant spatial patterns, with the number of tillers and plant height positively affecting both varieties. Additionally, the number of village unit cooperatives had a significant effect on Inpari 36. These findings provide spatial-based recommendations for improving rice productivity and food security policies in West Java.
Downloads
References
Asmarian, N., Ayatollahi, S. M. T., Sharafi, Z., & Zare, N. (2019). Bayesian spatial joint model for disease mapping of zero-inflated data with R-INLA: A simulation study and an application to male breast cancer in iran. International Journal of Environmental Research and Public Health, 16(22), 1–13. https://doi.org/10.3390/ijerph16224460
Besag, J., York, J., & Mollii~, A. (1991). Bayesian Image Restoration, With Two Applications in Spasial Statistics. Ann. Inst. Statist. Math, 43(1), 1–20. https://doi.org/10.1007/BF00116466
Bivand, R. S., Gómez-Rubio, V., & Rue, H. (2014). Approximate Bayesian inference for spatial econometrics models. Spatial Statistics, 9(C), 146–165. https://doi.org/10.1016/j.spasta.2014.01.002
Blangiardo, M., Cameletti, M., Baio, G., & Rue, H. (2013). Spatial and spatio-temporal models with R-INLA. In Spatial and Spatio-temporal Epidemiology (Vol. 4, Issue 1, pp. 33–49). https://doi.org/10.1016/j.sste.2012.12.001
BPS. (2018). Provinsi Jawa Barat Dalam Angka 2018 (D. Mulyahati, N. Komalasari, & V. Wahyuningrum, Eds.).
BPS. (2022). Provinsi Jawa Barat Dalam Angka 2022 (Y. Purbosari, Y. Anggorowati, & N. Suharno, Eds.).
BSIP Jawa Barat. (2023). Inpari 36 dan Inpari 37 Dari Tanah Bugis ke Tanah Pasundan Pembawa Berkah (Vol. 18).
Dejene, G., & Terdik, G. (2024). Processing Spatial Data for Statistical Modelling and Visualization Case study: INLA model for COVID-19 in Alabama, USA. Acta Technica Jaurinensis, 17(3), 130–142. https://doi.org/10.14513/actatechjaur.00746
Farid, A., Ugik, R., & Djoko, W. (2018). Faktor-Faktor yang Mempengaruhi Adopsi Petani dalam Penerapan Sistem Tanam Jajar Legowo di Desa Sukosari Kecamatan Kasembon Kabupaten Malang Provinsi Jawa Timur. Jurnal Penyuluhan, 14(1), 27–32. https://doi.org/10.22500/142018
Gracia, E., Supriatna, Nagasawa, R., Rokhmatuloh, Manessa, M., Kang, K., & Alidin, B. (2024). Spatial Phenology and Rice Productivity Estimation Based on Vegetation Indices in Wargasetra Village Using Planet Fusion Satellite Imagery. Papers in Applied Geography, 1–18. https://doi.org/10.1080/23754931.2024.2423287
Jaisyurahman, U., Desta Wirnas, D., Trikoesoemaningtyas, & Purnamawati, H. (2020). Dampak Suhu Tinggi terhadap Pertumbuhan dan Hasil Tanaman Padi. Jurnal Agronomi Indonesia, 47(3), 248–254. https://doi.org/10.24831/jai.v47i3.24892
Kadek, I., Putra, B., & Ayuningsasi, A. A. K. (2023). Peran Koperasi Unit Desa dalam Meningkatkan Kesejahteraan Petani di Kabupaten Jembrana. E-Jurnal EP Unud, 12(9), 586–599. https://doi.org/https://doi.org/10.24843/EEP.2023.v12.i09
Kadupitiya, H. K., Madushan, R. N. D., Gunawardhane, D., Sirisena, D., Rathnayake, U., Dissanayaka, D., Ariyaratne, M., Marambe, B., & Suriyagoda, L. (2022). Mapping Productivity-related Spatial Characteristics in Rice-based Cropping Systems in Sri Lanka. Journal of Geovisualization and Spatial Analysis, 6(2), 26. https://doi.org/10.1007/s41651-022-00122-0
Kunimitsu, Y., Kudo, R., Iizumi, T., & Yokozawa, M. (2016). Technological spillover in Japanese rice productivity under long-term climate change: evidence from the spatial econometric model. Paddy and Water Environment, 14(1), 131–144. https://doi.org/10.1007/s10333-015-0485-z
Larasati, I. F., & Hajarisman, N. (2020). Penerapan Spatial Autoregressive (Sar) Model pada Data Kemiskinan di Provinsi Jawa Barat Tahun 2019. Prosiding Statistika, 6(2). https://doi.org/10.29313/.v6i2.22829
Lestari, A. D., Sundahri, & Slameto. (2015). Karakterisasi Produktivitas Beberapa Varietas Padi (Oryza sativa L.) Pada Tiga Ketinggian Tempat Yang Berbeda. Berkala Ilmiah Pertanian , x.
Maulina, R. F., Djuraidah, A., & Kurnia, A. (2019). Pemodelan Kemiskinan di Jawa Menggunakan Bayesian Spasial Probit Pendekatan Integrated Nested Laplace Approximation (INLA). MEDIA STATISTIKA, 12(2), 140. https://doi.org/10.14710/medstat.12.2.140-151
Moraga, P. (2020). Geospatial Health Data; Modeling and Visualization with R-INLA and Shiny; Edition 1. https://doi.org/10.4324/9780429341823
Nuryanto, B., Priyatmojo, A., & Hadisutrisno. (2014). Pengaruh Tinggi Tempat dan Tipe Tanaman Padi terhadap Keparahan Penyakit Hawar Pelepah. Penelitian Pertanian Tanaman Pangan, 33(1). https://doi.org/10.21082/jpptp.v33n1.2014.p1-8
Papoila, A. L., Ribeiro, C., São João, R., Geraldes, C., Turkman, A. A., & Miranda, A. (2014). Stomach cancer incidence in Southern Portugal 1998-2006: a spatio-temporal analysis a Stomach cancer: a spatio-temporal analysis in Portugal. Biom.J, 56(3). https://doi.org/10.1002/bimj.201200264
Rachmawati, R. N., & Pusponegoro, N. H. (2021). Spatial Bayes Analysis on Cases of Malnutrition in East Nusa Tenggara, Indonesia. Procedia Computer Science, 179, 337–343. https://doi.org/10.1016/j.procs.2021.01.014
Rue, H., Martino, S., & Chopin, N. (2009). Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. In J. R. Statist. Soc. B (Vol. 71, Issue 2). https://academic.oup.com/jrsssb/article/71/2/319/7092907
Rusman, M. A. A., Darsono, & Ernoiz Antriyandarti, E. (2023). Analisis Forecasting Produksi Padi di Indonesia. 7(1).
Sailaja, B., Voleti, S. R., Subrahmanyam, D., Raghuveer Rao, P., Gayatri, S., Nagarjuna Kumar, R., & Meera, S. N. (2019). Spatial rice decision support system for effective rice crop management. Current Science, 116(3), 412–421. https://doi.org/10.18520/cs/v116/i3/412-421
Simatupang, P. (2007). Analisis Kritis Terhadap Paradigma dan Kerangka Dasar Kebijakan Ketahanan Pangan Nasional. Forum Penelitian Agro Ekonomi, 25(1), 1–18. https://doi.org/10.21082/fae.v25n1.2007.1-18
Simpson, D., Rue, H., Riebler, A., Martins, T. G., & Sørbye, S. H. (2017). Penalising model component complexity: A principled, practical approach to constructing priors. Statistical Science, 32(1), 1–28. https://doi.org/10.1214/16-STS576
Sucharidtham, T., & Wannapan, S. (2021). Technical Efficiency and Spatial Econometric Model: Application to Rice Production of Thailand BT - Behavioral Predictive Modeling in Economics (S. Sriboonchitta, V. Kreinovich, & W. Yamaka (eds.); pp. 333–350). Springer International Publishing. https://doi.org/10.1007/978-3-030-49728-6_22
Sudewi, S., Ala, A., & Farid, M. (2020). Keragaman Organisme Pengganggu Tanaman (OPT) pada Tanaman Padi Varietas Unggul Baru (VUB) dan Varietas Lokal pada Percobaan Semi Lapangan. Jurnal Agrikultura, 31(1), 15–24.
Sumastuti, E. (2010). Jiwa Entrepreneurship untuk Mewujudkan Ketahanan Pangan. Jejak, 3(1). https://doi.org/10.15294/jejak.v3i1.4667
Suphannachart, W. (2018). Spatial Analysis of Research-Productivity Nexus: A Case of Thai Rice Sector BT - Advances in Panel Data Analysis in Applied Economic Research (N. Tsounis & A. Vlachvei (eds.); pp. 1–12). Springer International Publishing.
Temaja, I. G. R. M., Sudana, M., Sudiarta, I. P., Susanta Wirya, G. N. A., & Puspawati, D. N. M. (2015). Pelatihan Pengabdian Penyakit Tungro dan Blas Pada Tanaman Padi di Subak Basangkasa. Udayana Mengabdi, 14(1), 1–37.
Usman, U., & Juliyani. (2018). Pengaruh Luas lahan, Pupuk, dan Jumlah Tenaga Kerja Terhadap Produksi Padi Gampong Matang Baloi. Jurnal Ekonomi Pertanian Unimal, 1(1). http://ojs.unimal.ac.id/index.php/JEPU
Yulina, N., Ezward, C., & Haitami, A. (2021). Karakter Tinggi Tanaman, Umur Panen, Jumlah Anakan dan Bobot Panen pada 14 Genotipe Padi Lokal. Jurnal Agrosains Dan Teknologi, 6(1). https://doi.org/10.36355/jsa.v6i1.496
Downloads
Published
Issue
Section
License
Copyright (c) 2025 I Putu Aditya Brama Putra Cakra Negara, Abdul Fakhar Ramadhani, Ahmad Abdurrazzaq (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
