<![CDATA[This study proposes the development of a sophisticated predictive system for pharmaceutical inventory management at Rakha Medika, Palembang, aimed at addressing the prevalent challenges associated with inaccurate drug stock forecasting. Employing the Trend Least Squares method, the system leverages historical consumption data to generate precise predictions of future pharmaceutical needs, thereby facilitating optimal procurement strategies and mitigating the risks of both stockouts and surplus inventory. Developed with PHP and MySQL, the system offers a user-friendly web-based interface, providing role-specific access for administrators, warehouse personnel, and senior management, ensuring seamless integration within the existing operational framework. This research highlights the importance of data-driven decision-making in healthcare supply chain management, where the accuracy of stock forecasts directly correlates with the quality-of-service delivery. Through rigorous testing using real-world data, the system demonstrated a significant improvement in forecasting accuracy and operational efficiency, with tangible benefits including reduced administrative burdens and enhanced drug availability. The implementation of this predictive system not only optimizes inventory control but also contributes to the overall enhancement of healthcare services at the public health center.]]>
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