Enhancing Data Accuracy for Student Eligibility in Government Support Through Data Analytics Platform
Bebania Rose Ann, Casals Bryan, Delos Santos Reynaldo Jr, Galimba Dominick John M, Gamilo Jenny B*, Llemit Joseph, Sengco Rome Criztoferson and Jed Concepcion
Abstract
In the current era of the Philippines, a nation facing with significant socioeconomic challenges, the effective implementation of social welfare programs stands as a critical project. With approximately thirteen million Filipinos living in poverty and a GDP-PPP per capita of ₱12,192 (Vera, 2024), the need for efficient governmental support systems has never been more pressing. The Department of Social Welfare and Development (DSWD) serves as the primary agency addressing these challenges through various initiatives, most notably the Pantawid Pamilyang Pilipino Program (4P's), which provides crucial educational and household support to underprivileged families [1].
The significance of this research lies in its potential to transform the management of social welfare programs in the Philippines, particularly the significant operational inefficiencies in the current manual systems of the 4P’s program. By addressing the current limitations of manual processes and introducing data analytics capabilities, this study not only aims to improve administrative efficiency but also seeks to ensure more effective targeting and delivery of educational and financial support to those who need it most.
