Educational Data Mining for Student Academic Performance Analysis

Authors

DOI:

https://doi.org/10.25047/jtit.v11i2.5627

Abstract

Good student academic performance is the key to success in the quality of education at university. One of the factors that influence academic success by utilising information technology and data analytics. This research incorporates GPA scores and other external factors that can affect students' academic performance such as parents’ job and latest education, address, gender, extracurricular, etc. This research uses Machine Learning; Decision Tree, Random Forest, K-Nearest Neighbour, Support Vector Classifier, Naive Bayes, and Gaussian as methods to analyse and predict the academic performance of students of the Information Systems Study Program, Faculty of Computer Science at the University of Jember. The results showed that the Decision Tree algorithm has the highest accuracy value of 0.9264 followed by Random Forest and K-Nearest Neighbour. Meanwhile, the prediction results show that the Decision Tree, K-nearest neighbour, and Random Forest algorithms can predict the same results.

Author Biographies

Khoirunisa Afandi, Universitas Jember

Khoirunnisa Afandi is a lecturer in the Information Systems Study Program at the Faculty of Computer Science, University of Jember. She earned her bachelor’s degree in Information Systems from the University of Jember and a master’s degree in Information Systems from the Institut Teknologi Sepuluh Nopember (ITS). Before entering academia, she worked as a systems analyst at PT Sebangsa Bersama, where she gained valuable industry experience that enriches her teaching and research. Her expertise includes information systems, data analysis, and system development, which she integrates into her academic contributions and classroom instruction.

M. Habibullah Arief, Universitas Jember

M. Habibullah Arief was born in Jember on February 11, 1992. He pursued his D3 in Informatics Management at Telkom University, Bandung, followed by an bachelor in Information Systems at Universitas Brawijaya, Malang, and an master degree in Computer Science, also from Universitas Brawijaya, Malang.

He has experience as a lecturer in the Information Systems Study Program at the Faculty of Computer Science, Universitas Jember, and as a Quality Assurance Staff at CV. Sinergi Spasial Indonesia. His research interests include Geographic Information Systems, focusing on applying spatial analysis in information systems to study phenomena.

Martiana Kholila Fadhil, Universitas Jember

Martiana Kholila Fadhil was born in Jember on July 19, 1999. She has experience as a lecturer in the Information Systems Study Program at the Faculty of Computer Science, Universitas Jember. She studied bachelor's degree in Information Systems at the University of Jember, and a master's degree in Information Systems at the Sepuluh November Institute of Technology. She has experience as an SPBE Surveyor at PT Tata Cipta Teknologi Indonesia. Her research interests include Information Systems, with a focus on IT adoption conducting the introduction and implementation of new IT applications.

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Published

2024-12-30

Issue

Vol. 11 No. 2 (2024): December

Section

Artikel