Analysis of Student Performance Using Data Mining Algorithm in Weka

Abstract: In this paper, Education Data Mining is significant in forecasting a student's academic progress in this article. In a forecasting information mining form, this article focuses on finding poor, medium, and quick learners among students and shows them using various approaches. Scholar details have been consulted, and a novice forecast has been performed using J48 and Random Tree in WEKA is an open-source technology. Assessment is based not just on academic success, but also on achievement in extracurricular sports. We can plainly assess a student's performance using both of these approaches.