Rainfall Prediction with Radial Basis Function Neural Network and Its Correlation with Bird's Eye Chili (Capsicum frutescens) Production in Sawangan Subdistrict Magelang Regency
Abstract
Climate change causes rainfall anomalies that directly impact the decline in horticultural crop productivity, particularly bird's eye chili (Capsicum frutescens). This study aimed to analyze the effect of global rainfall indices in Sawangan Subdistrict through the development a prediction model. Modeling was performed using Radial Basis Function Neural Network (RBFNN) method with Principal Component Analysis (PCA) integration to simplify the climate index input variables. Model accuracy was evaluated using the Root Mean Squared Error (RMSE), Nash-Sutcliffe Efficiency (NSE), and R2. Furthermore, the prediction results were correlated with chili production data to test the relevance of the model to actual conditions. Results showed that model configurations provide varying performance. The best model based on evaluation is the model in the 15-year range using PCA 3 global climate indices and training percentage of 90% (RMSE: 101.39; NSE: 0.7268). However, for validation and correlation with production, it was found that the 15-year range using PCA 5 global climate indices and training percentage of 70% was the best model with highest R2 value of 0.8572 and correlation value close to actual value. Variations in data period, number of climate indices, and training data proportion affect model performance. Adding data volume and variable complexity does not always improve accuracy, so it is necessary to identify the optimum point to get the most reliable prediction model.
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Agadinansyah, P.R. & Suciati, L.P. (2023). Adaptasi dan mitigasi petani cabai besar di Desa Sumberejo dalam menghadapi perubahan iklim. Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis, 9(2), 3016-3026. http://dx.doi.org/10.25157/ ma.v9i2.10813
Azam, M.G. & Rahman, M.M. (2022). Assessing spatial vulnerability of bangladesh to climate change and extremes: A geographic information system approach. Mitigation and Adaptation Strategies for Global Change, 27(6), 38. https://doi.org/10.1007/ s11027-022-10013-w
Azzahra, F., Samriana, S., & Ferdin, F. (2024). Pengaruh perubahan iklim terhadap pola hujan di Indonesia. Sindoro Cendikia Pendidikan, 3(1), 41-55.
Bhargawa, A. & Singh, A.K. (2021). Perceiving the trend of terrestrial climate change during the past 40 year (1978-2018). Journal of Atmospheric Science Research, 4(1), 1-15. https://doi.org/10.30564/jasr.v4i1.2488
BPS (Badan Pusat Statistik). (2024). Produksi Tanaman Sayur-Sayuran Menurut Kecamatan di Kabupaten Magelang (Kuintal). Badan Pusat Statistik, Magelang.
Dabanli, I., Şişman, E., Güçlü, Y.S., Birpınar, M.E., & Şen, Z. (2021). Climate change impacts on sea surface temperature (SST) trend around Turkey seashores. Acta Geophysica, 69, 295–305. https://doi.org/10.1007/s11600-021-00544-2
Duffy, C., Toth, G.G., Hagan, R.P.O., McKeown, P.C., Rahman, S.A., Widyaningsih, Y., Sunderland, T.C.H., & Spillane, C. (2021). Agroforestry contributions to smallholder farmer food security in Indonesia. Agroforestry Systems, 95, 1109–1124. https://doi.org/10.1007/s10457-021-00632-8
Fahmi, M., Siregar, A., & Effendi, I. (2023). Analysis of the supply and needs of red chili in North Sumatra Province. Jurnal Ekonomi, 12(1), 596–602.
Faisal, H.N. (2020). Peran penyuluhan pertanian sebagai upaya peningkatan peran kelompok tani (Studi kasus di Kecamatan Kauman Kabupaten Tulungagung). Jurnal Agribis, 6(1), 1-13.
Fawzy, S., Osman, A.I., Doran, J., & Rooney, D.W. (2020). Strategies for mitigation of climate change: A review. Environmental Chemistry Letters, 18, 2069–2094. https://doi.org/10.1007/s10311-020-01059-w
Kabbilawsh, P., Kumar, D.S., & Chithra, N.R. (2024). Assessment of temporal homogeneity of long-term rainfall time-series datasets by applying classical homogeneity tests. Environment, Development and Sustainability, 26, 16757–16801. https://doi.org/10.1007/s10668-023-03310-0
Kogo, B.K., Kumar, L., & Koech, R. (2021). Climate change and variability in Kenya : A review of impacts on agriculture and food security. Environment, Development and Sustainability, 23, 23–43. https://doi.org/10.1007/s10668-020-00589-1
Lastochkina, O., Aliniaeifard, S., SeifiKalhor, M., Bosacchi, M., Maslennikova, D., & Lubyanova, A. (2022). Novel approaches for sustainable horticultural crop production: Advances and prospects. Horticulturae, 8(10), 910. https://doi.org/10.3390/horticulturae8100910
Liao, Z. & Li, M. (2024). Comparing rainfall prediction at various time scales and rainfall interpolation at the regional scale using artificial neural networks. Theoretical and Applied Climatology, 155, 9929–9940. https://doi.org/10.1007/s00704-024-05205-0
Moeis, F.R., Dartanto, T., Moeis, J.P., & Ikhsan, M. (2020). A longitudinal study of agriculture households in Indonesia: The effect of land and labor mobility on welfare and poverty dynamics. World Development Perspectives, 20, 100261. https://doi.org/10.1016/j.wdp.2020.100261
Negara, H.R.P., Irzani, I., & Ripai, R. (2018). Konstruksi model matematika pola curah hujan menggunakan artificial neural network (ANN) dengan metode backpropagation. Jurnal Sains dan Teknologi, 1(1), 10-18.
Padmaningrum, D., Suminah, S., Utami, B.W., Ihsaniyati, H.,& Widiyanti, E. (2022). Pemberdayaan kelompok tani melalui budidaya cabai sebagai upaya peningkatan pendapatan petani lahan kering di Kabupaten Sukoharjo. Jurnal Pengabdian kepada Masyarakat, 13(1), 158-167. https://doi.org/10.26877/e-dimas.v13i1.7001
Pais, I.P., Reboredo, F.H., Ramalho, J.C., Pessoa, M.F., Lidon, F.C., & Silva, M.M. (2020). Potential impacts of climate change on agriculture – A review. Emirates Journal of Food and Agriculture, 32(6), 397-407. https://doi.org/10.9755/ejfa.2020.v32.i6.2111
Piekutowska, M., Niedbała, G., Piskier, T., Lenartowicz, T., Pilarski, K., Wojciechowski, T., Pilarska, A.A., & Czechowska-Kosacka, A. (2021). The application of multiple linear regression and artificial neural network models for yield prediction of very early potato cultivars before harvest. Agronomy, 11(5), 885. https://doi.org/10.3390/agronomy11050885
Polii, M.G.M., Sondakh, T.D., Raintung, J.S.M., Doodoh, B., & Titah, T. (2019). Kajian teknik budidaya tanaman cabai (Capsicum annuum L.) Kabupaten Minahasa Tenggara. Eugenia, 25(3), 73-77.
Saidah, H., Setiawan, A., Hanifah, L., Pradjoko, E., & Suroso, A. (2021). Koreksi bias data hujan luaran GCM ECHAM5 untuk prediksi curah hujan bulanan dan musiman Pulau Lombok. Jurnal Sains Teknologi & Lingkungan, 7(2), 209-219. https://doi.org/10.29303/jstl.v7i2.289
Santoso, A., & Nasir, M. (2021). Pemetaan lahan dan komoditas pertanian berbasis WebGIS di Kabupaten OKU Timur. Jurnal Ilmiah Betrik, 12(2), 129–139. https://doi.org/10.36050/betrik.v12i2.320
Sari, I., Yanti, N.D., & Hidayat, T. (2019). Faktor-faktor yang mempengaruhi usahatani cabai rawit (Capsicum fretescens L.) di Kabupaten Tabalong. Frontier Agribisnis, 3(4), 23-30. https://doi.org/10.20527/frontbiz.v3i4.1937
Susanto, A., Oetomo, W., & Wulandari, E. (2022). Analysis of satellite rain data usage on the rationalization activities of the rain post network (Case study: Rationalization of the jelai watershed rain post network). Journal of Research and Community Service, 3(14), 23-30. https://doi.org/10.36418/dev.v3i14.327
Thakur, N., Karmakar, S., & Soni, S. (2021). Rainfall forecasting using various artificial neural network techniques – A review. International Journal of Scientific Research in Computer Science, Engineering, dan Information Technology, 7(3), 506-526. https://doi.org/10.32628/CSEIT2173159
Wu, T. (2021). Quantifying coastal flood vulnerability for climate adaptation policy using principal component analysis. Ecological Indicators, 129, 108006. https://doi.org/10.1016/j.ecolind.2021.108006
Yuliana, A., Sujono, J., & Karlina. (2024). Analysis of extreme rainfall in the Mt. Merapi Area. Journal of the Civil Engineering Forum, 10(8), 73-84. https://doi.org/10.22146/jcef.10084
Zhang, L., Li, Y., Yu, S., & Wang, L. (2023). Risk transmission of el niño-induced climate change to regional green economy index. Economic Analysis and Policy, 79, 860-872. https://doi.org/10.1016/j.eap.2023.07.006
Ziaulhaq, W., & Amalia, D.R. (2022). Pelaksanaan budidaya cabai rawit sebagai kebutuhan pangan masyarakat. Indonesian Journal of Agriculture and Environmental Analytics (IJAEA), 1(1), 27-36. https://doi.org/10.55927/ijaea.v1i1.812
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