International Journal on Science and Technology

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Enhancing Inventory Control Through Sales Forecasting

Author(s) Mr. Rosito Dutosme Orquesta
Country Philippines
Abstract The study titled “Enhancing Inventory Control through Sales Forecasting for MSMEs in City Commercial Center (C3) Mall, Pagadian City” aimed to develop a computerized POS-integrated system with forecasting capabilities to improve inventory monitoring, sales tracking, and data-driven decision-making among MSMEs. Anchored on Knowledge Management Theory, Demand Forecasting Theory, and Time Series Forecasting Theory, the system was developed using the Agile Software Development Life Cycle (SDLC) to support iterative improvement and user-centered refinement.

This developmental research involved designing, coding, and testing a POS-integrated inventory system that automates business processes and provides sales forecasting using algorithms such as Moving Average, Linear Regression, Weighted Moving Average, Quadratic Regression, and Holt-Winters seasonal smoothing. The study was conducted at C3 Mall in Pagadian City, where 47 respondents, including MSME owners or managers, cashiers, inventory personnel, and IT professionals, evaluated the system using ISO/IEC 9126 software quality standards.

Results showed that the system achieved excellent performance across key quality parameters, including functionality, reliability, usability, efficiency, maintainability, portability, and security. Respondents confirmed its effectiveness in improving business operations by reducing manual errors, speeding up transactions, and enabling real-time forecasting and inventory monitoring. The system enhanced traditional POS platforms by transforming them into decision-support tools that improve operational efficiency and inventory planning.

This study contributes to Computer Science by demonstrating how forecasting algorithms and knowledge-based system design can support MSMEs in adopting digital transformation, enhancing operational efficiency, and maintaining sustainable and competitive business performance.
Keywords Expert System, Point-of-Sale (POS), MSMEs, CIPP, Sales Forecasting, Predictive Analytics, Business Intelligence, Digital Transformation, Demand Forecasting, Time Series Forecasting, Knowledge Management, Moving Average, Linear Regression, and Holt-Winters Seasonal Smoothing
Field Computer > Data / Information
Published In Volume 17, Issue 1, January-March 2026
Published On 2026-02-19
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