Application of Several Forecasting Method on Refined Sugar Production at PT. Perkebunan Nusantara X
DOI:
https://doi.org/10.24843/JBETA.2022.v10.i01.p03Keywords:
forecasting models, moving avarage, double exponential smoothing, accuracy testAbstract
Forecasting is the process of making a future prediction based on the present and past data using trend analysis. The purpose of this study was(1) to know historical pattern of refined sugar production, (2) to know what are the forecasting models that be used for prediction, (3) to get the best forecasting model by using accuracy test. This study use secondary data from PT Perkebunan Nusantara X and processing data by using Microsoft Excel. Based on analysis results exponential smoothing by using α = 0.8 is the best model. As comparison by using moving average with 2 period and double exponential smoothing with α = 0.6. The accuracy test of exponential smoothing α = 0.8 showing with value MAD = 2, MSE = 9, and MAPE = 36%. On validity test of forecasting models, exponential smoothing had showing value MAD = 1,025, MSE = 2,113,927, MAPE = 22%. Results of forecasting production with 6 period on the future is R1 = 5,106, R2 =5,047, R3 = 5,035, R4 = 5,032, R5 = 5,032, R6 = 5,032.
References
Apriawan, D. C., Irham, I., & Mulyo, J. H. (2015). Analisis produksi tebu dan gula di PT Perkebunan Nusantara VII (Persero). Agro Ekonomi, 26(2), 159–167.
Assauri, S. (2008). Manajemen produksi dan operasi. Lembaga Penerbit Fakultas Ekonomi Universitas Indonesia.
Auliasari, Kertaningtyas, & Kriswantono. (2019). Penerapan metode peramalan untuk identifikasi potensi permintaan konsumen. Informatics Journal, 4(3).
Christopher, M., & Holweg, M. (2011). Supply chain 2.0: Managing supply chains in the era of turbulence. International Journal of Physical Distribution & Logistics Management, 41(1), 63–82.
Etri, Desi, & Rito. (2016). Peramalan dengan metode exponential smoothing dari Brown (Studi kasus: Indeks Harga Konsumen Kota Samarinda). Jurnal Eksponensial, 7. Universitas Mulawarman.
Halimi, Anggraeni, & Tyasnurita. (2013). Pembuatan aplikasi peramalan jumlah permintaan produk dengan metode time series exponential smoothing Holt–Winters di PT Telekomunikasi Indonesia Tbk. Jurnal Teknik POMITS, 1. Institut Teknologi Sepuluh Nopember.
Handoko, T. H. (2000). Manajemen sumber daya manusia. BPFE.
Herjanto, E. (2008). Manajemen produksi dan operasi (Edisi ke-3). PT Grasindo.
Jung, H., & Jeong, S.-J. (2012). Managing demand uncertainty through fuzzy inference in supply chain planning. International Journal of Production Research, 50(19), 5415–5429.
Barus, J. H., & Ramli. (2012). Analisis peramalan ekspor Indonesia pasca krisis keuangan Eropa dan global tahun 2008 dengan metode dekomposisi. Jurnal Ekonomi dan Keuangan, 1(3), 117–133.
Makridakis, S., Wheelwright, S. C., & McGee, V. E. (2003). Metode dan aplikasi peramalan (Jilid 1, ed. revisi; terj.). Binarupa Aksara.
Maricar, M. (2019). Analisa perbandingan nilai akurasi moving average dan exponential smoothing untuk sistem peramalan pendapatan pada perusahaan XYZ. Jurnal Sistem dan Informatika, 13(2).
Novita, P. (2009). Peramalan jumlah air minum yang disalurkan PDAM Tirta Wampu Kabupaten Langkat tahun 2008–2010 dengan metode pemulusan eksponensial ganda. Universitas Sumatera Utara.
Putra, I. N. P., & Arvitrida, N. I. (2010). Peramalan permintaan dan perencanaan produksi dengan mempertimbangkan special event di PT CCBI Plant Pandaan. ITS Surabaya.
Rakhman, A., & Puspitasari, N. B. (2017). Usulan perbaikan perencanaan produksi produk engine tipe CJ untuk mobil pick up di PT XYZ dengan metode time series. Industrial Engineering Online Journal, 6(1).
Sembiring, L. J. (2017). Fakta penyebab Indonesia masih impor gula. Okezone. Diakses 3 Juli 2018.
Setyawan, E., Subantoro, R., & Prabowo, R. (2016). Analisis peramalan produksi karet (Hevea brasiliensis) di PT Perkebunan Nusantara IX Kebun Sukamangli Kabupaten Kendal. Mediagro, 12(2).
Sugiyanto, C. (2007). Permintaan gula di Indonesia. Universitas Muhammadiyah Surakarta.
Sungkawa, I., & Megasari, R. T. (2011). Nilai ramalan data deret waktu dalam seleksi model peramalan volume penjualan PT Satriamandiri Citramulia. ComTech, 2(2), 636–645.
Surihadi, A. A. (2009). Penerapan metode single moving average dan exponential smoothing dalam peramalan permintaan produk meubel jenis coffee table pada Java Furniture Klaten (Tugas akhir). Universitas Sebelas Maret.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
License Term
All articles published in Jurnal Beta (Biosistem dan Teknik Pertanian) are open access and licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This means that anyone is free to:
-
Share — copy and redistribute the material in any medium or format.
-
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
However, this is granted under the following conditions:
-
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
-
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
By submitting an article to Jurnal Beta (Biosistem dan Teknik Pertanian), authors agree to the publication of their work under this open access license. The authors retain the copyright of their work, but grant Jurnal Beta (Biosistem dan Teknik Pertanian) the right of first publication.
For more information about the CC BY 4.0 license, please visit the official website: https://creativecommons.org/licenses/by/4.0/
