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All Journal Agrikultura Jurnal Teknik Mesin Journal of Engineering and Management in Industrial System Rekayasa Sipil Jurnal Pengembangan Rekayasa dan Teknologi Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Aplikasia: Jurnal Aplikasi Ilmu-Ilmu Agama Jurnal INTECH Teknik Industri Universitas Serang Raya Buana Ilmu Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Journal of Industrial Engineering and Operation Management (JIEOM) Journal of Industial Engineering and Technology Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Teknika JUSTI (Jurnal Sistem dan Teknik Industri) JOSSE: Journal of Economics and Social Sciences Jurnal Teknologi dan Manajemen Sistem Industri De`Teksi : Jurnal Teknik Sipil Dedication : Jurnal Pengabdian Masyarakat Journal of Social Science and Economics
EKO WAHYU ABRYANDOKO
Univeritas Bojonegoro
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Transportation Other

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Mathematical Modeling for Climate-Based Optimization of Rice Planting Schedules Dawud, Moh Yusuf; Masahid; Abryandoko, Eko Wahyu
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 6 (2025): December 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v14i6.2285-2296

Abstract

The stability of rice production is greatly influenced by the dynamics of climate variability that changes rapidly and is unpredictable. This study developed a climate-based planting scheduling model that utilizes daily climate data and annual production data for the period 2016–2024. The predictive model was built through multiple linear regression to examine the effects of temperature, rainfall, humidity, and wind speed on crop yields and ARIMA to project climate and rice production until 2029. Data were obtained from BMKG, BPS, and related regional agencies, then processed to produce an adaptive planting schedule. The regression results showed high accuracy with R² = 0.99, Adjusted R² = 0.961, MAE = 5.980, and RMSE = 6.770. Rainfall showed a negative effect (p = 0.025) on rice production. The optimization model produced the two most profitable planting months each year and provided more stable yields than conventional planting patterns. Five-year production projections show fluctuations influenced by climate conditions, including a sharp decline in 2027 and a rebound in 2029. The development of an adaptive schedule model allows for alternative decision-making in areas vulnerable to climate change.
Co-Authors Ahmad Alfianul Karim Ahmad Ridho Ramadhani Ahmad Wiji Barokah Ahmad Wiji Barokah Ardana Putri Farahdiansari Ary Angga Fachreza ASHARI, FAISAL Budi Laksono, Galih Faisal Ashari Faisal Ashari Faisal Ashari Ichwan Hadi Saputra Khasanah, Naim Munah khoiriah, miftakhul Laksono, Galih Budi Lukmana, Priagung Maghfiroh, Amalia Ma’rifatu Masahid Masahid Masahid meckel rifaldo, mohammad Moh. Nurudduja Moh. Yusuf Dawud Muhammad Rozi Nirwanto, Bambang Nungki Dio Febriansa Pamuji, Imam Rahmadan, Eki Agtrin Rizky Stighfarrinata Sifa Bimananda, Ikhwan ST.,MT, Suji'at Sudirnanto, Sudirnanto Yulis Widhiastuti