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Submitted
February 18, 2021
Accepted
April 5, 2023
Published
June 26, 2023
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Abstract

PT. Indaco Warna Dunia is a decorative paint company in Indonesia that produces products under the brands Envi, Belazo, and Top Seal. Preliminary observations revealed that the forecasting method used by the company is ineffective and inaccurate. This inaccurate forecast result company’s problem in fulfilling the demand. This study aims to select the best forecasting method to improve forecast effectiveness and accuracy. The research was conducted at the Tarakan depot, and the products understudy were a fast-moving product category, specifically the Envi brand. Several forecasting methods such as Moving Average, Weighted Moving Average, Single Exponential Smoothing, Exponential Smoothing with Trend, and Holt's Double Exponential Smoothing. The accuracy of forecasting is the most important and it can be measured with MAPE (Mean Absolute Percentage Error). The results showed that Holt's Double Exponential Smoothing method is the best for three products, while the Exponential Smoothing with Trend method, and Single Exponential Smoothing method are the best for one of the products, respectively.

Keywords

Forecasting MAPE Moving Average Weighted Moving Average Single Exponential Smoothing Exponential Smoothing with Trend Holt’s Double Exponential Smoothing

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References

  1. Alfarisi, S. (2017). Sistem Prediksi Menggunakan Metode Single Exponential Smoothing. Journal of Applied Business and Economics, 4(1), 80–95.

  2. Chamid, A. A., & Murti, A. C. (2018). Prioritization of Natural Dye Selection In Batik Tulis Using AHP and TOPSIS Approach. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 12(2), 129. https://doi.org/10.22146/ijccs.29813

  3. Chamid, A. A., Surarso, B., & Farikhin, F. (2015). Implementasi Metode AHP Dan Promethee Untuk Pemilihan Supplier. Jurnal Sistem Informasi Bisnis, 5(2), 128–136. https://doi.org/10.21456/vol5iss2pp128-136

  4. Dewi, E. N. S., & Chamid, A. A. (2019). Implementation of Single Moving Average Methods For Sales Forecasting Of Bag In Convection Tas Loram Kulon. Jurnal Transformatika, 16(2), 113. https://doi.org/10.26623/transformatika.v16i2.1047

  5. Efe, İ. E., ÇOBAN, B., & FİRUZAN, E. (2018). Comparison of Single and Modified Exponential Smoothing Methods in the Presence of a Structural Break. Uluslararası İktisadi ve İdari İncelemeler Dergisi. https://doi.org/10.18092/ulikidince.354325

  6. Gusdian, E., Muis, A., & Lamusa, A. (2016). Peramalan Permintaan Produk Roti Pada Industri “ Tiara Rizki ” Di Kelurahan Boyaoge Kecamatan Kecamatan Tatanga Kota Palu. E-J, Agrotekbis, 4(1), 97–105.

  7. Kalekar, P. (2004). Time Series Forecasting Using Holt-Winters Exponential Smoothing. Kanwal Rekhi School of Information Technology, 04329008, 1–13. http://www.it.iitb.ac.in/~praj/acads/seminar/04329008_ExponentialSmoothing.pdf

  8. Kurniadi, W. (2018). Pendukung Keputusan Dalam Peramalan Penjualan Ayam Broiler dengan Metode Trend Moment dan Simple Moving Average Pada CV. Merdeka Adi Perkasa. Jurnal Media Informatika Budidarma, 2(3), 76–90. https://doi.org/10.30865/mib.v2i3.652

  9. Margi S, K., & Pendawa, S. (2015). Analisa Dan Penerapan Metode Single Exponential Smoothing Untuk Prediksi Penjualan Pada Periode Tertentu (Studi Kasus: PT.Media Cemara Kreasi). Prosiding SNATIF, 2(1998), 259–266.

  10. Nurlifa, A., & Kusumadewi, S. (2017). Sistem Peramalan Jumlah Penjualan Menggunakan Metode Moving Average Pada Rumah Jilbab Zaky. INOVTEK Polbeng - Seri Informatika, 2(1), 18. https://doi.org/10.35314/isi.v2i1.112

  11. Perry, M. B. (2010). The Weighted Moving Average Technique. Wiley Encyclopedia of Operations Research and Management Science. https://doi.org/10.1002/9780470400531.eorms0964

  12. Sinaga, H., & Irawati, N. (2018). A Medical Disposable Supply Demand Forecasting By Moving Average And Exponential Smoothing Method. 1–5. https://doi.org/10.4108/eai.24-1-2018.2292378

  13. Utari, H., Mesran, & Silalahi, N. (2016). Perancangan Aplikasi Peramalan Permintaan Kebutuhan Tenaga Kerja Pada Perusahaan Outsourcing Menggunakan Algoritma Simple Moving Average. Jurnal TIMES, 5(2), 1–5. http://ejournal.stmik-time.ac.id/index.php/jurnalTIMES/article/view/546

  14. Vlasov, V. M., Novikov, A. N., Novikov, I. A., & Shevtsova, A. G. (2018). Definition of Perspective Scheme of Organization of Traffic Using Methods of Forecasting and Modeling. IOP Conference Series: Materials Science and Engineering, 327(4). https://doi.org/10.1088/1757-899X/327/4/042116

  15. Yapar, G., Capar, S., Selamlar, H. T., & Yavuz, I. (2018). Modifed Holt’s Linear Trend Method. 47(5), 1394–1403.