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Aryafi, Javiery Khansa
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Chemical Engineering, Chemistry & Bioengineering Chemistry Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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ANALISIS METODE FORECASTING UNTUK MENINGKATKAN PENJUALAN BAKPIA LESTARI MALANG Aryafi, Javiery Khansa; Mahendaringratry, Ayudya
jurnal ATMOSPHERE Vol. 6 No. 1 (2025): ATMOSPHERE
Publisher : Teknik Kimia ITN Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/atmosphere.v6i1.14774

Abstract

This research aims to forecast the sales of bakpia products at UMKM Bakpia Lestari Malang to support production planning to be more optimal. The main problems faced are fluctuations in demand and limited production capacity caused by the implementation of a hybrid system, which is a combination of Make to Stock and Make to Order. A quantitative approach is used in this research by processing sales data for one year, and comparing five forecasting methods, namely Single Moving Averages, Weighted Moving Averages, Exponential Smoothing, Trend Projection, and Exponential Trend. The accuracy of each method is evaluated using Mean Absolute Deviation (MAD) and Mean Squared Error (MSE) indicators. The analysis results show that the Exponential Smoothing method with (α = 0.5) produces the lowest error rate, namely MAD of 55.56 and MSE of 10796.74. Therefore, this method is recommended as the best approach for forecasting sales in June 2025. These results are expected to be a reference for UMKM in managing the production process more efficiently and on target.
Co-Authors Ayudya Mahendaringratry