WebPy-BudgetAnalytics: Budget Monitoring and Analytic Support Tool for State Universities and Colleges - Rodriguez, Adrian A.; Dela Fuente, Michael B. (International Journal of Computing Sciences Research; Vol 8 (2024): Volume 8, 2024)
Purpose - This study aims to develop a web-based budget monitoring system with an analytic support tool using a multiple linear regression model to enhance the financial management system of state universities and colleges (SUCs).| Method - It follows a descriptive and developmental design to answer the research problem and attain the objective of the study. The descriptive design is applied in the documentary analysis and administration of the survey using survey questionnaires. The developmental approach is applied in developing the web-based software, specifically, the Rapid Application Development (RAD) model. Results - The study provided ways to address the present problems and difficulties with the current method of managing financial resources: (a) automating budget execution-related processes; (b) recording of budget execution in a central database; (c) real-time monitoring of budget utilization; and (d) projection and forecast of future budget requirements based on previous utilization records for budget planning and preparation. Conclusion – The developed system is highly acceptable in terms of functionality, usability, reliability, maintainability, and efficiency in managing university financial resources based on user evaluation. Recommendation - The system includes the following features for the recommendation to be implemented: (1) preparation and management of working financial plan (WFP); (2) preparation and management of sub-allotment; (3) preparation and management of obligation and utilization request; (4) preparation, management, and monitoring of Certificate of Availability of Funds (CAF) request; and (5) reports preparation, budget monitoring and projection of future budgetary requirements. Research Implications – The study demonstrates how automation of processes and applying multiple linear regression enhance the management and monitoring of SUC financial resources.