Proceedings of the 17th International Conference on Humanities, Psychology and Social Sciences
Year: 2024
DOI:
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Development of BulSU OPIS with Demand Allocation Forecasting Model Using Exponential Smoothing Algorithm
Rommel S. Pabustan MIT
ABSTRACT:
The study explores the development and evaluation of the BulSU Online Procurement and Inventory System (BulSU OPIS), integrated with a Demand Allocation Forecasting Model powered by the Exponential Smoothing Algorithm, designed to enhance procurement efficiency and inventory management at Bulacan State University. While the system demonstrated exceptional technical performance in areas such as functional suitability (4.58), security (4.69), and maintainability (4.76), user perceptions of usefulness (2.14) and ease of use (2.17) highlighted significant barriers to adoption. Key challenges included a steep learning curve, technical complexity, and insufficient alignment with user workflows. Recommendations include enhanced user training, interface refinement, iterative feedback integration, and incremental feature deployment to bridge the gap between technical capabilities and user satisfaction. The study emphasizes the potential of integrating advanced forecasting techniques into educational procurement systems, fostering operational efficiency, and aligning institutional processes with global standards.
keywords: Demand Allocation Forecasting, Exponential Smoothing Algorithm, Procurement Optimization, E-Procurement Systems, Educational Resource Management, System Usability, Inventory Management Efficiency