Forecasting Book Inventory Needs at CV. Irmandiri Pustaka Using Holt-Winters Method

Abstract

This study aims to forecast inventory needs at CV. Irmandiri Pustaka using the Holt-Winters Multiplicative method. The company distributes Student Worksheets (LKS), with seasonal demand that rises at the start of each semester. Accurate forecasting is crucial to manage inventory efficiently and avoid overstocking or shortages. Holt-Winters was chosen for its ability to capture both trend and seasonal patterns. The forecast uses sales data from January 2024 to June 2025. Forecast accuracy is evaluated using Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Error (MSE). Initial parameter settings produced high errors, prompting optimization through Excel’s Solver feature. The optimized parameters α = 0.01, β = 0.01, and γ = 0.04 reduced the MAPE to 25.19%. These results show that the Holt-Winters method can provide reliable inventory forecasts, especially after the second seasonal cycle, and serve as a helpful tool for inventory planning decisions.