The Implementation of Single Moving Average and Double Exponential Smoothing Methods for Sales Forecasting at Ludin Mart Pottery Store - Nur Firdaus, Iqbal Alif; M. Ghofar Rohman; M. Rosidi Zamroni (Journal of Artificial Intelligence and Engineering Applications (JAIEA), 2025)
Increasing business competition driven by rapid technological development requires Micro, Small, and Medium Enterprises (MSMEs) to implement effective sales strategies. One approach was sales forecasting, which supports accurate business decision-making. This study was conducted at Toko Gerabah Ludin with the aim of applying and comparing two forecasting methods: Single Moving Average (SMA) and Double Exponential Smoothing (DES), to predict product sales. The data used consisted of monthly sales from July 2024 to May 2025. The SMA method with a period of 3 produced a sales prediction for Rice Flour in June 2025 of 108.33, with a Mean Absolute Percentage Error (MAPE) of 7.36%. Meanwhile, the DES method produced a forecast of 115.92 with a MAPE of 7.8%. Based on the accuracy evaluation using MAPE, the SMA method provided slightly more accurate results compared to DES for the given dataset. Therefore, the SMA method was considered more suitable for short-term sales forecasting in Toko Gerabah Ludin. This research was expected to serve as a reference for MSME practitioners in selecting the appropriate and efficient forecasting method to support stock planning and business strategy.