Comparison of Weighted Moving Average (WMA) and Single Exponential Smoothing (SES) Methods in Website-Based Sales Forecasting (Case Study: Adi Comp Store) - Faizin, M Rahmat; M. Ghofar Rohman; M. Rosidi Zamroni, (Journal of Artificial Intelligence and Engineering Applications (JAIEA), 2025)
This study aimed to compare two forecasting methods, namely Weighted Moving Average (WMA) and Single Exponential Smoothing (SES), in predicting sales at Toko Adi Comp through a web-based system. The WMA method used three periods with weights of 3, 2, and 1, while the SES method applies a smoothing parameter (Alpha) of 0.2. The forecasting process utilized historical sales data from January 2024 to April 2025, covering ten different laptop products. The system automatically calculates predictions and displays the Mean Squared Error (MSE) to evaluate the accuracy of each method. The test results showed that the SES method produces lower MSE values in 7 out of 10 analyzed products, such as the Hp 14-Ck0xxx, which has an MSE of 13.2282, compared to the WMA method with an MSE of 15.1068. Although generally less accurate, WMA performed well on some products such as Asus X442U. This comparison indicated that SES was more stable and responsive to gradual changes in sales trends. Therefore, SES was recommended as the primary forecasting method in the sales prediction system for Toko Adi Comp. This system is expected to support inventory planning, optimize stock levels, and improve sales decision-making.