Penerapan Metode Single Exponential Smoothing untuk Prediksi Penjualan Kacamata pada Optik Adis - Ade Rizka; Gilang Kurniawan; Adriel Ageva Andanov Pinem (Bulletin of Information Technology (BIT), 2026)
Accurate inventory management is a crucial factor in supporting the sustainability of retail businesses, including those in the optical industry. Precision in determining the quantity of eyeglass inventory has a significant impact on operational efficiency and customer satisfaction. Optik Adis still faces challenges in estimating eyeglass stock requirements due to the manual process of recording and analyzing sales data. This situation has the potential to cause overstock conditions, leading to increased warehouse costs, or conversely, stock shortages that result in lost sales opportunities. Based on these issues, this study aims to develop an eyeglass sales prediction platform to support managerial decision-making in inventory management. The forecasting method used is Single Exponential Smoothing (SES) because it is suitable for sales data that fluctuates relatively stably. The system development process refers to the Waterfall methodology, which includes requirement analysis, system design, implementation, testing, and maintenance. Sales data from February to November 2025 were used as the basis for computation, with testing variations of the alpha parameter ranging from 0.1 to 0.9. The research findings reveal that an alpha value of 0.1 produces the best prediction performance with a Mean Absolute Percentage Error (MAPE) value of 19.06%, which falls into the “Good” category, and a Mean Absolute Deviation (MAD) value of 3.536 units. The application of the method in the system projects eyeglass sales in December 2025 at 17.50 units. Black Box testing shows that all system functions operate properly. Thus, the implementation of the method can help Optik Adis plan stock procurement more accurately, effectively, and efficiently.