Students’ Performance Prediction using Artificial Neural Network
Nahdatul Akma Ahmad, Najmul Hassan, Harlina Suzana Jaafar, Nur Idawati Md Enzai
Abstract
Abstract This paper proposed a method for predicting diploma students’ performance of Faculty of Electrical Engineering (EE), Universiti Teknologi MARA (UiTM) Terengganu. Data of 59 first semester students from Electrical Engineering (EE) were obtained to predict students’ academic performance. A predictive model based on a machine learning technique was employed. The predictive model utilizes Artificial Neural Network (ANN) technique that was developed to predict the actual performance of first semester students based on Sijil Pelajaran Malaysia (SPM) results, first semester results, and the interest level of the participants towards EE course. The findings have shown that the developed model could accurately predict the actual result of the first semester students successfully with minimal errors.