Analysis on Students’ Academic Performance in Relation to The Results of Pre-University Examination
Keywords:Student Performance, Paired t test, Z test, Data Mining, Classification and Regression Tree, K-Nearest Neighbors, Naïve Bayes
There is a great deal of uncertainty regarding the factors that influence their final year grade, which includes their entry qualification. This paper investigates the impact of entry qualification and pre-university CGPA on student performance at the university level. Entry qualifications are critical for educational institutions or educational providers to ensure the quality of the graduates. The goal of this study is to analyze and compare performance of Bachelor of Science (Industrial Statistics) with Honours (BWQ) students. Total of 54 students were selected form the Faculty of Applied Sciences and Technology (FAST), Universiti Tun Hussein Onn Malaysia (UTHM). The students are coming from Malaysian Higher School Certificate (STPM) and Malaysian Matriculation Programme. Paired t test and Z test were carried out to analyze the impact of pre-university’s CGPA and each semester’s GPA as well as impact of entry qualification towards their final year grade. Classification and Regression Tree (CART), K-Nearest Neighbors and Naïve Bayes were used to develop and predict the students’ performance. The findings show that there is no relation between the result obtained from previous semester towards the next semester. Meanwhile, students from STPM outperform Matriculation in terms of their GPA per semester, pre-university CGPA as well as their final CGPA. The K-Nearest Neighbors and Naïve Bayes models have been documented as the most efficient data mining techniques in predicting student performance with the highest percentage of accuracy of 100%.