Alalay sa Impormasyon: Process-Documentation and Preliminary Assessment on Barangay San Juan ACCFAS’ Data Management
Barangay data management systems in the Philippines have evolved to enhance governance and service delivery by streamlining processes, ensuring data accuracy, and improving communication. However, many barangays still struggle with inefficient, manual data management methods that compromise security, accessibility, and centralization. This study examines the implementation of a new data management system for Barangay San Juan ACCFA, a collaborative initiative between Manuel V. Gallego Foundation Colleges (MVGFC) and local stakeholders. The project aims to restore and digitize community records following the barangay’s loss of access to a previous digital system, improving administrative efficiency and accuracy. Evaluation of the current system reveals significant deficiencies, with critical scores (1.00–1.50) across key quality dimensions, including functionality, usability, security, and performance. These shortcomings render the system ineffective and unsustainable, highlighting the need for a comprehensive overhaul. Despite delays caused by Typhoons Kristine and Pepito, addressing these deficiencies remains a priority to ensure long-term functionality and sustainability. Beyond improving local governance, this project serves as a practical learning platform for students, bridging academic theory with real-world application. Using the Community-Based Participatory Action Research (CBPAR) methodology, the initiative fosters community engagement, inclusivity, and empowerment. It also aligns with MVGFC’s mission to produce competent, ethical, and socially responsible graduates. By restoring a reliable digital data management system, this collaboration strengthens barangay operations, enhances service delivery, and contributes to MVGFC’s broader vision of sustainable community development and transformative governance.
Authors
- Angelo Sera
- Ruiz Gómez Andrés Alberto
- A. Domínguez Sevilla
- Rene Boy Abiva
- John Carlo Azarcon
- Jaya Krissia Mae Donato
- Jeffrey Marigmen
Publication Details
- Journal
- Social science lens
- Published
- 2025-02-27
- DOI
- https://doi.org/10.62718/vmca.ssl-wjhdsr.4.1.sc-0225-006
- Primary Topic
- demographic modeling and climate adaptation
- Type
- article
- Field-Weighted Citation Impact
- 0.00