Cooperation Unit - Timorese Academic Journal of Science & Technology

Abstract: Improving the mathematics ability is of the most important for engineering students to face rapid technological developments such as machine learning, data science, Artificial Intelligence (AI), Big Data and other related works. In this study, we perform the series of test to evaluate the importance of the attributes. The results show that the attribute of student age impacts the outputs. We find out that using the Random Forest Algorithm is efficient for the prediction, helping the teachers to identify the weakness of the students in mathematics performance.

Keywords: Data Mining, Students Performance, Random Forest Algorithm and Predictive Analytics