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October 22, 2025Open Access

Information System of Warehouse Management Web-Based with Forecasting Features Using Single Exponential Smoothing Method at Pilar Mas Building Supply Store

Key Points

The system improves demand forecasting, reducing stock imbalances and enhancing operational efficiency.
Forecasting accuracy was achieved with an average mean absolute percentage error of 19.28% across key products.
The implementation of the single exponential smoothing method supports precise inventory management in non-seasonal contexts.
Integrating web-based functionalities facilitates easier tracking of incoming and outgoing goods for better inventory control.

Abstract

This study aims to develops a web-based warehouse management system with forecasting features using the Single Exponential Smoothing (SES) method at Pilar Mas Building Supply Store. The store often experiences overstocking or stockouts due to the lack of accurate demand forecasting. SES was chosen for its simplicity, responsiveness to recent data, and suitability for non-seasonal demand patterns. The system provides functions for inventory management, recording incoming and outgoing goods, and automated sales forecasting. Forecast accuracy was evaluated using the Mean Absolute Percentage Error (MAPE), with an average value of 19.28% across 10 main products, indicating good accuracy. The results demonstrate that the system can generate reliable demand forecasts, support inventory planning, reduce stock imbalances, and enhance operational efficiency.

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