Student Academic Performance Prediction System (SAPPS) скачать в хорошем качестве

Student Academic Performance Prediction System (SAPPS)

In today's digital era, accurately predicting student performance is crucial for educational institutions in order to identify at-risk students and provide timely interventions. While various models have been proposed for student performance prediction, there is a lack of sophisticated models that can guide stakeholders in taking appropriate measures to address student problems. To address this gap, we adopted the RepTree algorithm, a decision tree-based machine learning approach, to develop the Student Academic Performance Prediction System (SAPPS) for the University Poly-Tech Malaysia (UPTM). The system's predictive capabilities empower educational institutions to identify students who are likely to face academic difficulties and proactively take measures to improve their outcomes. #iRIE2023 #ARI.UiTM