WEB-BASED RICE HARVEST PREDICTION SYSTEM USING FUZZY MAMDANI METHOD: A CASE STUDY IN MAGELANG CITY
DOI:
https://doi.org/10.61677/jth.v3i4.757Abstract
This study discusses the application of the Fuzzy Inference System method to predict rice yields in Magelang City as an effort to support food security planning. The data used included harvest area, production, and productivity with the period 2021–2022 as training data and 2023–2024 as test data. The prediction process is carried out through the stages of fuzzification, formation of fuzzy rules, inference using min–max operators, and defuzzification using the centroid method. The prediction system is designed to be web-based so that it can be used by farmers, government agencies, and related parties in decision-making. The results of the study show that the Fuzzy Mamdani method is able to produce predictions that are close to actual data with a low error rate. For example, the prediction of 109.20 tons in a harvest area of 18 Ha is close to the actual data of 106.56 tons, and an RMSE value of 1.43 tons is obtained which is better than the seasonal naïve and linear regression methods. With stable accuracy and flexibility in updating regulations, this system is suitable for use as an agricultural planning tool, especially for food distribution strategies, planting planning, and rice stock management in Magelang City.
References
Arifin, Z., Sukaris, S., & Santoso, R. A. (2024). Tiktok Impact: Decoding Fashion Purchase Choices In Generation Z Through Social Media Strategies And Product Innovation. Jurnal Pekommas, 9(2), 225–232. https://doi.org/10.56873/jpkm.v9i2.5505
Aziz, G. R. (2024). Luas Panen dan Produksi Padi di Kota Magelang 2023. Badan Pusat Statistik.
Burhanuddin, A. (2023). Analisis Komparatif Inferensi Fuzzy Tsukamoto, mamdani dan Sugeno Terhadap Produktivitas Padi di Indonesia. LEDGER: Journal Informatic and Information Technology, 2(1), 48–57. https://doi.org/10.20895/ledger.v2i1.1013
Fairus, Putri, S. A., & Muliani, F. (2023). Application of Mamdani Fuzzy Method To Predict the Amount of Pine Resin Production. Barekeng, 17(1), 411–416. https://doi.org/10.30598/barekengvol17iss1pp0411-0416
Lutfi, A., Suwarno, J., Yuliana, Y., & Anwar, A. N. (2024). Penerapan Logika Fuzzy Mamdani Untuk Menentukan Stok Beras Di Toko Ijal Jaya Berbasis Web. Jurnal Informatika Utama, 2(1), 72–80. https://doi.org/10.55903/jitu.v2i1.179
Nasution, V. M., & Prakarsa, G. (2020). Optimasi Produksi Barang Menggunakan Logika Fuzzy Metode Mamdani. Jurnal Media Informatika Budidarma, 4(1), 129. https://doi.org/10.30865/mib.v4i1.1719
Nuraini, D., Violina, D., Anamisa, D. R., Khotimah, B. K., Jauhari, A., & Mufarroha, F. A. (2025). Prediksi Hasil Panen Padi dengan Metode Multiple Linear Regression dan Particle Swarm Optimization untuk Meningkatkan Produksi Padi di Madura. JUSIFOR : Jurnal Sistem Informasi Dan Informatika, 4(1), 1–8. https://doi.org/10.70609/jusifor.v4i1.5857
Rahayu, Y. S., Saputra, Y., & Irawan, D. (2024). Implementasi Metode Waterfall Pada Pengembangan Sistem Informasi Mobile E-Disarpus. ZONAsi: Jurnal Sistem Informasi, 6(2), 523–534. https://doi.org/10.31849/zn.v6i2.20538
Saleh, M. (2024). The Evolution of Fashion Content On Tiktok: From 2020 to 2024 In Malaysia. Journal of Creative Arts, 1(2), 74–81. https://doi.org/10.24191/jca.v1i2.1567
Septyono, M. B., Prasetyo, A. D., Pratama, B. R., & Sari, A. P. (2023). Penerapan Metode Mamdani Untuk Prediksi Produksi Padi di Pulau Sumatra. Seminar Nasional Informatika Bela Negara (SANTIKA), 3, 2747–0563.
Siagian, D. G., Katrin Jenny Sirait, Anggiat Parlindungan Simbolon, & Jamardua Haro. (2025). Comparative study of sugeno fuzzy method and mamdani fuzzy method for rice stock optimization at Perum BULOG North Sumatra regional division. Desimal: Jurnal Matematika, 8(2), 325–336. https://doi.org/10.24042/a7jvnx56
Swasono, M. A. H., Dianta Mustofa K., & Muthmainah, H. N. (2023). Pemanfaatan Teknologi Informasi dalam Optimalisasi Produksi Tanaman Pangan: Studi Bibliometrik Skala Nasional. Jurnal Multidisiplin West Science, 2(08), 668–683. https://doi.org/10.58812/jmws.v2i08.589
Tauhid, G. F., Wangni, W. A., Adinata, R. D., Dinargo, R., Saputra, M. D. J., & Rahman, A. (2025). Fuzzy Logic dalam Keputusan Jumlah Produksi Berbasis Website Dengan Metode Mamdani. Jurnal Inovasi Komputer (INOKOM), 1(2), 56–65. https://doi.org/10.71200/inokom.v1i2.34
Wibowo, Y., & Mukammila, R. M. (2022). Perencanaan Produksi Kopi Robusta (Coffea canephora) Menggunakan Metode Logika Fuzzy (Studi Kasus di PT. Perkebunan Nusantara XII Kebun Silosanen) Robusta Coffee (Coffea canephora) Production Planning Using Fuzzy Logic Methods (Case Study At PT. Perkebuna. JOFE : Journal of Food Engineering | E-ISSN, 1(4), 191.
Wulandari, W., Makmur, H., & Surianto, D. F. (2024). Analysis of Fuzzy Mamdani Implementation in Decision Making of Agricultural Plant Types for Farmers. Sistemasi, 13(2), 841. https://doi.org/10.32520/stmsi.v13i2.3612
Yuliyani, L., Salam, R., Bahar, R. R., Hartoyo, T., & Pramita, D. A. (2023). Analisis Efisiensi Usahatani Padi Berdasarkan Musim Di Indonesia Efficiency Analysis Of Rice Farming Based On Seasons In Indonesia. Jurnal Agristan, 5(2), 345–367. https://doi.org/10.37058/agristan.v5i1.7117
Zulfa, E. I., Ferryan, D. A., & Novitasari, D. C. R. (2022). Analisis Pendekatan Statistik Dan Fuzzy Mamdani Dalam Prediksi Produktivitas Padi. Majalah Ilmiah Matematika Dan Statistika, 22(1), 105–117. https://doi.org/10.19184/mims.v22i1.30304
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