Enrollment Trend Analysis and Forecasting (ETAF): Leveraging Data Visualization to Optimize Resource Management

Abstract

This study addresses the inefficiencies of traditional enrollment monitoring and reactive academic planning at Silay Institute, Inc. by introducing the Enrollment Trend Analysis and Forecasting (ETAF) System. The system provides a secure, desktop-based decision-support platform that centralizes historical student records and automates enrollment analytics. A key feature is the predictive forecasting tool designed to support strategic resource planning, utilizing single and double exponential smoothing models, complemented by customizable reporting functions that strengthen strategic decision-making and operational efficiency. Operating strictly as a read-only platform over a secure Local Area Network (LAN), the system completely eliminates manual data entry errors and file manipulation vulnerabilities. By replacing outdated manual methods, this localized digital solution ensures data accuracy, reliability, and strict compliance with the Data Privacy Act of 2012 (RA 10173). Ultimately, the project highlights the role of modern administrative technologies in enhancing institutional outcomes, reinforced by evaluations of system performance, security protocols, and user training for effective institutional adoption. System evaluation under the ISO/IEC 25010 quality standard and Pomel Scale achieved an overall performance rating of “Excellent” (mean score of 4.66) led by functionality (4.78), usability (4.72), and security (4.81), with compatibility rated as a highly satisfactory “Good” (4.43).