Prediksi hasil panen padi berdasarkan data curah hujan, suhu, dan kelembapan dengan metode ARIMA

Authors

  • Angellika Kristy Menteng Universitas Mercu Buana Yogyakarta
  • Anief Fauzan Rozi Universitas Mercu Buana Yogyakarta

DOI:

https://doi.org/10.31571/saintek.v14i1.9292

Keywords:

Prediksi Panen Padi, Curah Hujan, Suhu, Kelembapan, ARIMA, Analisis Deret Waktu

Abstract

Penelitian ini bertujuan untuk memprediksi produksi padi di Kabupaten Banggai menggunakan metode ARIMA berbasis data historis pada tahun 2004 hingga 2025. Model ARIMA(3,1,2) dipilih berdasarkan evaluasi kombinasi parameter dan menghasilkan nilai Mean Absolute Percentage Error (MAPE) sebesar 10,87%. Nilai ini menunjukkan akurasi yang lebih baik dibandingkan metode Fuzzy Time Series 20,40% dan Triple Exponential Smoothing 291,79%. Model kemudian diimplementasikan dalam sistem sederhana yang memungkinkan input variabel tahun, curah hujan, suhu, dan kelembapan untuk menampilkan hasil prediksi. Namun, model yang digunakan masih bersifat univariat dan hanya mengandalkan data historis tanpa memasukkan variabel iklim secara langsung. Hasil penelitian ini menunjukkan bahwa ARIMA dapat menjadi pendekatan awal yang cukup andal dalam peramalan produksi padi, namun penelitian lanjutan disarankan untuk mengembangkan model multivariat seperti ARIMAX atau SARIMA dan melakukan uji validasi menggunakan data real-time.

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Author Biographies

Angellika Kristy Menteng, Universitas Mercu Buana Yogyakarta

Program Studi Sistem Informasi, Fakultas Teknologi Informasi

Anief Fauzan Rozi, Universitas Mercu Buana Yogyakarta

Program Studi Sistem Informasi, Fakultas Teknologi Informasi

References

Adin Musababa, M. (2024). Implementasi algoritma linear regression untuk prediksi produksi tanaman padi di Kabupaten Grobogan. Data Sciences Indonesia (DSI), 3(2), 68–78. https://doi.org/10.47709/dsi.v3i2.3118

Darwati, I., & Hayuningtyas, R. Y. (2023). Metode simple moving average dan weighted moving average dalam memprediksi produksi beras. Evolusi: Jurnal Sains Dan Manajemen, 11(2), 34–41. https://doi.org/10.31294/evolusi.v11i2.17267

Defiyanti, S., Sari, B. N., Padilah, T. N., Karawang, U. S., Kawarang, K., Korespondensi, P., Hujan, C., & Tanam, W. (2024). Optimasi pertanian padi: Peramalan curah hujan berbasis ARIMA. Jurnal Teknologi Informasi Dan Ilmu Komputer, 11(6), 1377–1384. https://doi.org/10.25126/jtiik.2024118682

Faisal Muhammad, T. A., & Irawan, M. I. (2023). Implementasi long short-term memory (LSTM) untuk prediksi intensitas curah hujan (Studi kasus: Kabupaten Malang). Jurnal Sains Dan Seni ITS, 12(1). https://doi.org/10.12962/j23373520.v12i1.106892

Farismana, R. (2024). Penerapan k-means clustering untuk pemetaan produktivitas padi dan prediksi panen di Kabupaten Indramayu. Journal of Information System, Applied, Management, Accounting and Research, 8(3), 589. https://doi.org/10.52362/jisamar.v8i3.1572

Febiola, A., Dewi, A., Fazarin, F. M., Ramadhani, F., Khaffi, M. A., Akbar, R., & Dalimunthe, D. Y. (2024). Perbandingan metode ARIMA dan SARIMA dalam peramalan jumlah penumpang bandara Provinsi Kepulauan Bangka Belitung. Jambura Journal of Mathematics, 6(2), 160–168. https://doi.org/10.37905/jjom.v6i2.25081

Mifthasha, S. (2024). Peramalan jumlah sampah terangkut di Kota Pekanbaru menggunakan metode ARIMA. Indonesian Council of Premier Statistical Science, 3(2), 71. https://doi.org/10.24014/icopss.v3i2.32272

Pangestu, A., Irma Purnamasari, A., & Ali, I. (2024). Analisis peramalan tingkat pengangguran terbuka di Jawa Barat: Pendekatan time series menggunakan metode ARIMA. Jurnal Ilmu Komputer Dan Teknologi, 5(1), 18–25. https://doi.org/10.35960/ikomti.v5i1.1298

Pratama, G. R. S., & Pratama, I. (2023). Penjadwalan masa tanam padi dan jagung berdasarkan hasil prediksi curah hujan menggunakan ARIMA di wilayah Sleman. Jurnal Informatika Dan Teknik Elektro Terapan, 11(3s1), 859–868. https://doi.org/10.23960/jitet.v11i3s1.3375

Putri, S. M., & Arliani, E. (2022). Peramalan produksi padi di Kabupaten Sleman menggunakan model ARIMA. Jurnal Kajian Dan Terapan Matematika, 8(3), 188. http://dx.doi.org/10.21831/jktm.v8i3.19082

Santoso, J. R., & Wijaya, H. (2024). Implementasi data mining untuk sales forecasting berbasis website dengan metode ARIMA. Journal Binary Digital - Technology, 7(1). https://doi.org/10.32877/bt.v7i1.1332

Saragih, E. S., Fridz Meryatdas Gumay, Meisya Fajriyanti, Samuel Eurico Siregar, & Winalia Agwil. (2024). Perbandingan metode fuzzy time series dan ARIMA dalam peramalan hasil panen kopi. Diophantine Journal of Mathematics and Its Applications, 3(2), 118–125. https://doi.org/10.33369/diophantine.v3i2.32049

Vasella, A., Gusti, S. K., Handayani, L., & Ramadhani, S. (2023). Perbandingan metode peramalan Crude Palm Oil menggunakan ARIMA dan Triple Exponential Smoothing. Jurnal Informatika Universitas Pamulang, 8(2), 236–246. https://doi.org/10.32493/informatika.v8i2.30979

Widyatmoko, E. T., Kadekoh, I., & Hadid, A. (2024). Analisis kesesuaian lahan berdasarkan faktor iklim dan topografi untuk tanaman padi sawah di Kabupaten Poso. Buletin GAW Bariri (BGB), 5, 15–24. https://doi.org/10.31172/bgb.v5i2.125

Yuliyani, L., Salam, R., Bahar, R. R., Hartoyo, T., & Pramita, D. A. (2023). Analisis efisiensi usahatani padi berdasarkan musim di Indonesia. Jurnal Agristan, 5(1), 74–87. https://doi.org/10.37058/agristan.v5i1.7117

Zamahzari, A., & Puryantoro, P. (2023). Forecasting produksi padi dan konsumsi beras di Provinsi Jawa Timur. Jurnal Pertanian Cemara, 20(1), 27–38. https://doi.org/10.24929/fp.v20i1.2542

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Published

2025-06-30

How to Cite

Menteng, A. K., & Rozi, A. F. (2025). Prediksi hasil panen padi berdasarkan data curah hujan, suhu, dan kelembapan dengan metode ARIMA. Jurnal Pendidikan Informatika Dan Sains, 14(1), 150–159. https://doi.org/10.31571/saintek.v14i1.9292

Issue

Vol. 14 No. 1 (2025): Jurnal Pendidikan Informatika dan Sains

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Copyright (c) 2025 Angellika Kristy Menteng, Anief Fauzan Rozi

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