ANALISIS PERFORMANSI METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DALAM PENGENDALIAN PERSEDIAAN SUSU
Abstract
This study aims to address the issue of milk inventory control at PT. Indodairy Continental by applying the Autoregressive Integrated Moving Average (ARIMA) method. The uncertainty in milk demand, influenced by changes in consumer consumption patterns and market fluctuations, poses challenges in accurate production and distribution planning. This research uses historical milk sales data from the past several years to build an ARIMA model. The data undergoes several steps, including data collection and plotting, stationarity testing using ACF and PACF, differencing, and parameter estimation of the ARIMA model. The analysis results indicate that the data is stationary, and the ARIMA (1,0,0) model is selected as the best model based on the significance test. This model is used to forecast milk sales for the next six months. The predictions indicate an increase in monthly sales, allowing the company to optimize production and distribution processes, reduce costs, and improve customer satisfaction.
References
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[2] V. M. M. Siregar and E. D. Siringo-Ringo, “Decision Support System to Determine Scholarship Recipients Using the Electre Method,” COSTA J. (Computer Sci. Technol. Appl. Journal), vol. 1, no. 2, pp. 39–49, 2023.
[3] V. M. M. Siregar and E. D. Siringo-Ringo, “Decision Support System to Determine Scholarship Recipients using Analytical Hierarchy Process Method,” COSTA J. (Computer Sci. Technol. Appl. Journal), vol. 1, no. 1, pp. 39–49, 2023, doi: 10.35335/idss.v4i2.67.
[4] V. M. M. Siregar and M. A. Hanafiah, “Perancangan Aplikasi Augmented Reality Untuk Edukasi Penerapan Konsep Green Economy Dalam Pengembangan Desa Wisata Sebagai Upaya Mewujudkan Pembangunan Berwawasan Lingkungan,” J. TEKINKOM, vol. 6, no. 2, pp. 339–348, 2023, doi: 10.37600/tekinkom.v6i2.950.
[5] N. A. Sinaga et al., “Decision support system with MOORA method in selection of the best teachers,” AIP Conf. Proc., vol. 2453, no. July, 2022, doi: 10.1063/5.0094437.
[6] V. M. M. Siregar et al., “Decision support system for selection of food aid recipients using SAW method,” AIP Conf. Proc., vol. 2453, no. July, 2022, doi: 10.1063/5.0094385.
[7] C.Pradeepkumar and S.Loganathan, “Penerapan Metode Asosiasi Menggunakan Algoritma Apriori Pada Aplikasi Pola Belanja Konsumen ( Studi Kasus Toko Buku Gramedia Bintaro ),” Int. J. Sci. Eng. Res. (IJ0SER), vol. 3, no. 4, p. 2, 2015.
[8] S. Isnanto and S. Widodo, “Penerapan Data Mining Pada Penerimaan Mahasiswa Baru Dengan Algoritma K-Means Clustering,” J. Tek. Inf. dan Komput., vol. 4, no. 2, p. 158, 2021, doi: 10.37600/tekinkom.v4i2.367.
[9] F. Ramdhani and K. Setiawan, “Penerapan Data Mining untuk Prediksi Pelanggan di PT. XYZ Menggunakan Algoritma Linear Regression,” MALCOM Indones. J. Mach. Learn. Comput. Sci., vol. 4, no. 2, pp. 490–497, 2024, doi: 10.57152/malcom.v4i2.1217.
[10] M. A. Pratama, W. Priatna, T. S. Lestari, O. Aritonang, A. Hidayat, and L. Regression, “PENERAPAN ALGORITMA LINEAR REGRESSION PADA PREDIKSI PENJUALAN PRODUK TERLARIS DI PT,” vol. 0, no. 3, 2023.
[11] W. Purba et al., “Penerapan Data Mining Untuk Pengelolaan Data Rekam Medis Menggunakan Metode K-means Clustering Pada Rumah Sakit Royal Prima Medan,” J. TEKINKOM, vol. 6, no. 1, pp. 158–168, 2023, doi: 10.37600/tekinkom.v6i1.857.
[12] A. Azhari, “Peramalan Jumlah Nasabah Menggunakan Metodeboxjenkins(Arima),Holt-Winters Exponential Smoothingdan Fuzzy Time Series,” J. Ilm. Indones., vol. 7, no. 10, 2022.
[13] V. P. Ramadhan and F. Y. Pamuji, “Analisis Perbandingan Algoritma Forecasting dalam Prediksi Harga Saham LQ45 PT Bank Mandiri Sekuritas (BMRI),” J. Teknol. dan Manaj. Inform., vol. 8, no. 1, pp. 39–45, 2022, doi: 10.26905/jtmi.v8i1.6092.
[14] Biorxiv n2, “No 主観的健康感を中心とした在宅高齢者における 健康関連指標に関する共分散構造分析Title,” vol. 1, no. 1, pp. 4–6, 2024.
[15] A. Septhiani, “Analisis Perbandingan Algoritma Supervised Learning untuk Prediksi Kasus Covid-19 di Jakarta,” J. Sains Komput. Inform. (J-SAKTI, vol. 7, no. 2, pp. 583–594, 2023.
[16] S. P. Fauzani and D. Rahmi, “Penerapan Metode ARIMA Dalam Peramalan Harga Produksi Karet di Provinsi Riau,” J. Teknol. dan Manaj. Ind. Terap., vol. 2, no. 4, pp. 269–277, 2023, doi: 10.55826/tmit.v2i4.283.
[17] L. Nur Komara and Dwi Agustin Nuriani Sirodj, “Metode Autoregressive Integrated Moving Average (ARIMA) untuk Meramalkan Produksi Padi di Provinsi Jawa Tengah,” Bandung Conf. Ser. Stat., vol. 3, no. 2, pp. 496–504, 2023, doi: 10.29313/bcss.v3i2.8442.
[18] S. Suseno and Suryo Wibowo, “Penerapan Metode ARIMA dan SARIMA Pada Peramalan Penjualan Telur Ayam Pada PT Agromix Lestari Group,” J. Teknol. dan Manaj. Ind. Terap., vol. 2, no. I, pp. 33–40, 2023, doi: 10.55826/tmit.v2ii.85.
[19] M. Rianto and R. Yunis, “Analisis Runtun Waktu Untuk Memprediksi Jumlah Mahasiswa Baru Dengan Model Random Forest,” Paradig. - J. Komput. dan Inform., vol. 23, no. 1, 2021, doi: 10.31294/p.v23i1.9781.
[20] S. A. Sinaga, “Implementasi Metode Arima (Autoregressive Moving Average) Untuk Prediksi Penjualan Mobil,” J. Glob. Technol. Comput., vol. 2, no. 3, pp. 102–109, 2023, doi: 10.47065/jogtc.v2i3.4013.
Published
2024-06-30
How to Cite
TAJRIN, Tajrin; HENDRA, Hendra; GURNING, Juan Fernando.
ANALISIS PERFORMANSI METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DALAM PENGENDALIAN PERSEDIAAN SUSU.
Jurnal Tekinkom (Teknik Informasi dan Komputer), [S.l.], v. 7, n. 1, p. 481-486, june 2024.
ISSN 2621-3079.
Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/1222>. Date accessed: 04 dec. 2024.
doi: https://doi.org/10.37600/tekinkom.v7i1.1222.
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