Andi Rukmana

Work place: Universitas Insan Pembangunan Indonesia, Jl. Raya Serang KM 10, Tangerang, Indonesia

E-mail: andirukmana@gmail.com

Website: https://orcid.org/0009-0000-1205-8267

Research Interests:

Biography

Andi Rukmana Lecturer at Insan Pembangunan Indonesia University. The fields of science studied are information technology, information systems and software engineering. The subjects taught include software engineering, cloud computing, graphic design and operational engineering.

Author Articles
Prediction of Student Graduation Based on Academic Achievement Index and Gender Using the C4.5 Classification Method

By Giri Reksa Guritno Winanti Beby Tiara Andi Rukmana Nurasiah

DOI: https://doi.org/10.5815/ijieeb.2025.05.02, Pub. Date: 8 Oct. 2025

Many study programs at universities face issues, including students experiencing delays in graduation, which hinders the completion of their studies on time. These delays in student graduation contribute to a decrease in the accreditation score of the Information Systems program. One solution to address this issue is to develop a data-mining-based system to monitor and utilize student progress data by predicting their graduation status using the C4.5 Decision Tree algorithm. This research process involves several stages: problem analysis, data and system design, coding, testing, and finally, maintenance. The outcome of this research is the implementation of the C4.5 algorithm to predict students' timely and delayed graduation. The data used includes records of students who graduated in 2021 and 2022. The acceptance rate, calculated using a confusion matrix, demonstrates an accuracy level of 92.16%, based on a dataset of 119 training data points and 51 testing data points, or 70% training to 30% testing ratio. The results of this research and testing indicate that the C4.5 Decision Tree algorithm is highly suitable for predicting student graduation outcomes.

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