SRCB GUIDANCE MANAGEMENT SYSTEM WITH APPOINTMENT SCHEDULING AND MACHINE LEARNING FOR STUDENTS’ SOCIO-ECONOMIC STATUS PREDICTION

Educational institutions increasingly adopt digital systems to enhance administrative efficiency and improve student support services. This study developed the SRCB Guidance Management System with Appointment Scheduling and Machine Learning for Students’ Socio-Economic Status Prediction to address challenges in manual guidance operations at St. Rita’s College of Balingasag. Utilizing the Scrum methodology, the system was designed and implemented to streamline student profiling, counseling appointment management, entrance examination processing, and reporting. A key feature integrates supervised machine learning to predict students' socio-economic status based on Personal Data Sheet inputs, supporting early identification of learners who may require financial or psychosocial interventions. The system incorporates role-based modules for Super Admin, Admin/Guidance Counselor, Guidance Advocates, Students, and Examinees, and employs technologies including PHP, Python (Scikit-Learn), MySQL, Tailwind CSS, Bootstrap, and XAMPP. System functionality and usability were evaluated through functional testing and the System Usability Scale (SUS), yielding scores above 90%, indicating excellent usability and positive user acceptance. Findings demonstrate that the system enhances guidance operations, reduces manual workload, allows convenient appointment scheduling, and provides data-driven insights for student welfare support. This study offers an innovative approach to educational guidance services by integrating predictive analytics, contributing to more efficient, accessible, and responsive student support systems. Future enhancements may include expanding machine learning datasets, strengthening mobile optimization, and integrating automated counseling support tools.

Keywords: Guidance System; Appointment Scheduling; Machine Learning; Socio-Economic Status; Student Profiling; Counseling; Web-Based System

Available at: SRCB College Library