<![CDATA[Purpose – This study aims to develop a Web-Based Work-Based Learning Management System with an Early Monitoring System and Learning Analytics at SMKN 5 Makassar to address the issues surrounding the management of work-based learning, which is still conducted manually, leading to delays in data processing, difficulties in monitoring student activities, and limitations in real-time competency evaluation. Methods – This study employed the Research and Development (R&D) method using the Prototype development model, consisting of requirements analysis, system design, implementation, testing, and maintenance. The developed system was evaluated based on the ISO/IEC 25010 software quality standard, including functional suitability, usability, performance efficiency, reliability, security, maintainability, compatibility, and portability. Findings – The research results show that the developed system successfully integrates vocational training administration, student placement, attendance monitoring, daily journals, the Early Monitoring System, and Learning Analytics into a single web-based platform. The results of the software quality evaluation show that the system achieved a Functional Suitability score of 100%, a Usability score of 92.18%, a Performance Efficiency score with a GTMetrix Grade of B, a Performance Score of 72%, a Structure Score of 98%, and a page load time of 2.6 seconds. Reliability testing using Apache JMeter showed an error rate of 0%, while security testing using Acunetix revealed no security vulnerabilities, with the following categories: High = 0, Medium = 0, Low = 0, and Informational = 0. Research Implications – This study is limited to internship management activities at SMKN 5 Makassar and has not yet been integrated with other academic information systems. Future studies may expand the implementation scope and integrate advanced analytics features. Originality – The novelty of this research lies in the integration of an Early Warning System and Learning Analytics into a single web-based vocational training management platform that enables real-time detection of student risks based on attendance data and the consistency of daily journals, and supports data-driven monitoring and decision-making by supervising teachers.]]>
