Optimizing 4Ps Beneficiary Identification: A Web - Based Analysis Using Forecasting and Multiple Linear Regression to Improve Socioeconomic Outcomes

The limited application of advanced analytics in social welfare programs hinders effective beneficiary identification and reduces the potential for optimizing socioeconomic outcomes. Addressing this gap, our paper introduces a web-based application designed to enhance the Pantawid Pamilyang Pilipino Program (4Ps) by utilizing multiple regression and forecasting techniques to improve decision-making in identifying program beneficiaries. By analyzing key socioeconomic data, the application generates actionable insights that support program administrators and policymakers, thereby enabling more accurate, data-driven decision-making. The application has been developed and is designed with a user-friendly interface that allows clients and stakeholders to easily navigate the system while accessing essential information. To ensure its robustness and reliability, the application was evaluated according to the ISO/IEC 25010 software quality model, receiving high scores across several dimensions, including functionality, performance efficiency, compatibility, reliability, usability, and security. Such evaluations underscore the application's capability to meet diverse user needs effectively. The findings suggest that this tool not only supports efficient beneficiary identification but also offers a scalable solution for broader social welfare programs. Future recommendations include the integration of more advanced analytics, enhancements in data visualization for better interpretability, and expansion of the platform's scalability to accommodate a growing user base and larger datasets, ensuring the system's adaptability and long-term viability in socioeconomic planning initiatives.