Student performance evaluation plays a significant role in improving the quality of education and supporting academic decision-making in educational institutions. Every institution collects a large amount of academic data, including attendance, assignment marks, internal assessment scores, and semester examination results. However, these data are often maintained only as records and are not fully utilized for performance evaluation. This research proposes a Student Performance Analytics System that adopts a data-driven approach to analyze and evaluate students' academic performance. The proposed system collects, organizes, and processes student data to generate meaningful insights through statistical analysis and graphical visualization. It enables educators to monitor academic progress, identify top-performing students, and recognize students who require additional academic support. The system also helps reduce manual effort and improves the accuracy of academic evaluation. The findings of this study demonstrate that data analytics can effectively support educational institutions in making informed decisions and enhancing student performance management. Overall, the proposed system provides a simple, reliable, and efficient solution for academic performance evaluation.

Keywords:

Student Performance Analytics, Academic Performance Evaluation, Data Analytics, Student Records, Attendance Analysis, Assignment Evaluation, Educational Analytics, Data Visualization.