Optimizing Enrollment and Administrative Decision-making through Data Analysis for Local Universities and Colleges

  • Rex Valiña Diaz College of Computer Studies, Laguna State Polytechnic University, Philippines
  • Archieval M. Jain College of Computer Studies, Laguna State Polytechnic University, Philippines

Abstract

Purpose – Local universities and colleges (LUCs) often face recurring challenges in managing enrollment and generating data-driven administrative decisions due to limited analytical tools. These inefficiencies affect institutional performance and student satisfaction. This study aimed to develop a data-driven enrollment and administrative decision-making system for Balian Community College, intended to serve as a model for other LUCs.

Method – The study employed a system development approach using the Agile methodology. Institutional data were processed using predictive and prescriptive analytics and integrated into a customized decision support system. System quality was assessed following ISO/IEC 25010 standards, while user acceptance was evaluated through the Technology Acceptance Model (TAM).

Results – System evaluation generated high ratings in software quality, with mean scores of 4.68 for functionality, 4.55 for usability, and 4.60 for efficiency. TAM results showed strong user acceptance, with perceived usefulness rated at 4.70 and perceived ease of use at 4.66. The system streamlined enrollment workflows, reduced administrative workload by around 35%, and provided actionable insights that improved decision-making and resource allocation.

Conclusion –The developed system effectively addressed key administrative challenges by integrating data analytics into institutional operations. However, its implementation was limited to a single LUC, suggesting a need for broader validation.

Recommendations – Future research should refine the system’s predictive models, integrate advanced analytics features, and test scalability across multiple LUCs to enhance robustness and interoperability.

Research Implications – Findings demonstrate the potential of analytics-driven systems to strengthen institutional planning, resource management, and evidence-based decision-making in higher education.

Practical Implications – Implementing data-driven platforms can substantially improve enrollment efficiency, reduce manual workload, and enhance transparency in administrative processes, thereby supporting better service delivery in LUCs.

Social Implications – Improved institutional efficiency may lead to better student experiences and more equitable access to quality education within local communities.

Author Biographies

Rex Valiña Diaz, College of Computer Studies, Laguna State Polytechnic University, Philippines

Mr. Rex V. Diaz is an Information Technology Instructor at Balian Community College. He earned his Bachelor of Science in Computer Science and Certificate of Teaching Proficiency (CTP) from Laguna State Polytechnic University, Siniloan Host Campus. With a strong background in computer science and education, he has been actively involved in promoting the integration of technology in teaching and administrative processes. Mr. Diaz currently serves as the Office of Student Affairs and Services (OSAS) Coordinator at Balian Community College, where he contributes to student development and institutional initiatives. His research interests include system development, data analytics, and educational technology aimed at optimizing academic and administrative operations in higher education.

Archieval M. Jain, College of Computer Studies, Laguna State Polytechnic University, Philippines

Dr. Archieval M. Jain is an Associate Professor at the Laguna State Polytechnic University, Siniloan Campus. He earned his Doctor of Information Technology from the University of the East, Manila. He also holds a Master of Information Technology and a Master of Arts in Education, reflecting his strong foundation in both technical and pedagogical disciplines. His baccalaureate degree is a Bachelor of Science in Computer Science. Dr. Jain currently serves as the Program Coordinator of the Bachelor of Science in Information Technology program and as the Extension Implementing Unit Head of the Extension and Training Services at the College of Computer Studies. His professional interests include information systems development, technology integration in education, and community-based ICT initiatives.

Published
2025-12-13
How to Cite
DIAZ, Rex Valiña; JAIN, Archieval M.. Optimizing Enrollment and Administrative Decision-making through Data Analysis for Local Universities and Colleges. International Journal of Computing Sciences Research, [S.l.], v. 9, p. 4074-4098, dec. 2025. ISSN 2546-115X. Available at: <//stepacademic.net/ijcsr/article/view/797>. Date accessed: 27 may 2026.
Citation Formats
Issue
Vol 9 (2025): Volume 9
Section
Articles
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