Predicting Chicken Egg Production Using the Seasonal Autoregressive Integrated Moving Average (SARIMA) Method at PT. PULAU MANDIRI JAYA FARM
DOI:
https://doi.org/10.31004/jestm.v6i1.383Keywords:
ACF Analysis, SARIMA Model, Seasonal Forecasting, Egg Production, Time SeriesAbstract
Chicken egg production at PT. Pulau Mandiri Jaya Farm for the 2021-2024 period showed significant monthly fluctuations (2,140-6,890 tons) due to seasonal patterns and feed management challenges, requiring accurate time series forecasting for optimal planning. This study aims to predict egg production using the SARIMA(1,1,1)(1,1,1,12) model to capture annual seasonality. This quantitative descriptive study analyzed monthly univariate data from 48 observations, with purposive sampling (80% training: 38 months; 20% testing: 10 months). Data analysis used Python statsmodels for stationarity testing, ACF/PACF identification, model fitting, and MSE evaluation. The results showed excellent model performance (MSE=0.3262; Ljung-Box p=0.44; Jarque-Bera p=0.65), accurately predicting 2025 production (3,886-6,873 tons). In conclusion, the SARIMA model enables precision feed stock planning (60-70% of production costs), improving operational efficiency and food security in South Sumatra.
References
Arifianti, R. (2020). Pengertian strategi produksi dan keputusan strategi produksi/operasi. Universitas Padjadjaran.
Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.
Durrah, F. I., Yulia, Y., Parhusip, T. P., & Rusyana, A. (2018). Peramalan jumlah penumpang pesawat di Bandara Sultan Iskandar Muda menggunakan metode SARIMA (Seasonal Autoregressive Integrated Moving Average). Jurnal Analisis Data, 1(1), 1–11. https://doi.org/10.24815/jda.v1i1.11847
Emzir. (2021). Metodologi penelitian kuantitatif. Prenada Media.
Hudzaifah, M., & Rismayadi, A. A. (2021). Peramalan arus lalu lintas berdasarkan waktu tempuh dan cuaca menggunakan metode time series decomposition. Jurnal Responsif: Riset Sains dan Teknologi, 3(2), 207–215. https://doi.org/10.51977/jti.v3i2.559
Kusyanto, Suhardi, D., & Awaluddin, R. (2020). Peramalan penjualan keramik menggunakan metode moving average dan exponential smoothing pada usaha Agus Keramik. Jurnal Ekonomi Akuntansi dan Manajemen (JEAM), 1(1), 12–21. https://journal.uniku.ac.id/index.php/jeam
Muhamad, I. M., Wardana, S. A., & Wanto, A. (2022). Algoritma machine learning untuk penentuan model prediksi produksi telur ayam petelur di Sumatera. Journal of Informatics, Electrical and Electronics Engineering, 1(4), 126–134. https://djournals.com/jieee/article/view/382
Nuriyana. (2020). Model pengendalian persediaan pakan ayam broiler. Jurnal Mirai Management, 5(1), 2597–4084.
Nurulita. (2020). Penerapan metode peramalan ARIMA (Autoregressive Integrated Moving Average) untuk penentuan tingkat safety stock pada industri elektronik [Skripsi, Universitas Indonesia]. Perpustakaan Universitas Indonesia. https://lib.ui.ac.id/abstrakpdf?id=20250041&lokasi=lokal
Sari, M. P. (2021). Penggunaan metode ARIMA (Autoregressive Integrated Moving Average) untuk prakiraan penderita pneumonia balita di Kota Semarang tahun 2019–2021 [Skripsi, Universitas Negeri Semarang]. Institutional Repository UNNES.
Sudaryono. (2024). Prosedur analisis time series dan validasi model statistik. Rajawali Pers.
Sugiyono. (2022). Metode penelitian kuantitatif, kualitatif, dan R&D (3rd ed.). Alfabeta.
Suyono, A. A., Kusrini, K., & Arief, M. R. (2022). Prediksi indeks harga konsumen komoditas makanan di Kota Surabaya menggunakan Support Vector Regression. Metik Jurnal, 6(1), 45–51. https://doi.org/10.47002/metik.v6i1.339
Tarisya, T. P. J., & Primandari, A. H. (2023). Perbandingan metode double exponential smoothing dan metode triple exponential smoothing untuk harga telur pada produsen di Kabupaten Sukabumi. Emerging Statistics and Data Science Journal, 1(2), 204–214. https://doi.org/10.20885/esds.vol1.iss.2.art21
Zuhdi, F., Nurjanah, D., & Rahly, F. (2023). Peramalan produksi telur itik di Provinsi Aceh dengan pendekatan Autoregressive Integrated Moving Average. Jurnal Veteriner, 24(1), 22–31. https://doi.org/10.19087/jveteriner.2023.24.1.2
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Daniel Prasetyo
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
