Predictive modelling for student's academic performance in Sultan Idris Education University based on respective locality during Covid-19 using support vector machine (SVM).

The Coronavirus Disease 2019 (COVID-19) outbreak–first emerged in December 2019–has left a mark on how people throughout the world live, particularly students at educational institutions. Those students had to prepare for the rest of their studies emotionally and physically by adjusting to virtual teaching and learning methods, which could make a substantial impact on their academic achievement. As a result, this study was carriedout to investigate students' academic performance expectations depending on their various localities during the pandemic to forecast their academic success for the following semester. This research enables a variety of steps to be constructed to improve and maintain students' achievement in their learning activities. The research involved university students from the University of Education Sultan Idris' Faculty of Science and Mathematics. The Support Vector Machine model was used to predict a student's academic performance based on the respective locality in this paper. [ABSTRACT FROM AUTHOR]