Prediction Students’ Performance in Elective Subject Using Decision Tree Method

  • Suhainy binti Sulaiman Politeknik Ungku Omar, Malaysia
Keywords: Data Mining, Classfication, Decision Tree


In polytechnic system, a student must take the elective subjects at least 3 subjects to complete their study. The elective subjects were chosen based on their interest and first come first serve. The result obtained for elective subjects in final examination will affect their future. It is important to predict whether they pass or fail in final examination. Literature survey (LS) was used to obtain the information about students’ profile and current approaches in predicting the students’ performance using data mining. In this paper, the researcher uses data mining which is decision tree method to predict the students’ performance in elective subject. The aim of this research is to evaluate the students result in choosing the correct elective subjects. This research is focused on the ICT students who select DBM3033 as an elective subject. Two phases involved which are prepossessing data and mining data. RapidMiner software is used in mining data process. Classification technique is applied for decision tree method. The research findings showed that students whose result weak in both SPM Mathematics and DBM1033 are predicted as fail in final examination for DBM3033.