Analysis on students performance using naïve

Classification of students’ academic performance for Sijil Pelajaran Malaysia (SPM) at early stage of their previous study will able to help in identify the students’ achievement to will assist the educators and school management taking the necessary actions. In this research, data mining techniques are used to classify students’ of Maktab Rendah Sains MARA (MRSM) Kuala Berang performance based on their performance in certain subjects. The aim of this study is to examine the Naive Bayes algorithm which is one of the classification methods in data mining, to identify the hidden information between subjects that affected the performance of students in Sijil Pelajaran Malaysia (SPM). Data was collected from the second semester obtained from year 2011 until 2014 with the total of 488 students’ data were used to train the algorithm. It has been shown that with 10 cross fold-validation that Naive Bayes algorithm can be used for classification of students’ performance in early stages of second semester with an accuracy of 73.4%.