This study examined the inefficiencies in the manual purchasing and inventory systems at a State University, which have resulted in issues such as supply overstocking, expired inventory, and misallocation of budgetary funds. To address these challenges, the researcher developed the State University Online Procurement and Inventory System (OPIS), which incorporates a Demand Allocation Forecasting Model based on the Exponential Smoothing Algorithm. The research employed a developmental approach, integrating agile software development with descriptive methodologies, including surveys and user observations. The assessment of the OPIS utilized quality parameters consistent with ISO 25010 standards and the Unified Theory of Acceptance and Use of Technology (UTAUT). The findings indicate that the OPIS significantly enhanced procurement efficiency, resulting in a 35% reduction in stock wastage and a 20% decrease in order costs, which ultimately led to a 15% reduction in forecast errors. Furthermore, the system improved supplier performance, optimized budget usage, and streamlined the procurement process. However, users encountered challenges due to the system's complex interface and their unfamiliarity with its functionalities. Consequently, this study recommends that state universities implement user-centric training programs, enhance the system interface, and establish ongoing feedback mechanisms to facilitate effective utilization. Additionally, this research advocates for the comprehensive adoption of intelligent purchasing tools within university contexts to foster operational efficiency, accountability, and cost-effectiveness.
Rommel Pabustan (Thu,) studied this question.
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