Predicting Student Loyalty in Higher Education Using Machine Learning: A Random Forest Approach
Student loyalty is a crucial factor supporting the sustainability of higher education institutions. The aim of this study is to predict student loyalty using a machine learning approach, specifically the random forest algorithm. The data for this research were collected through a questionnaire that...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Informatics Department, Faculty of Computer Science Bina Darma University
2025-03-01
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| Series: | Journal of Information Systems and Informatics |
| Subjects: | |
| Online Access: | https://journal-isi.org/index.php/isi/article/view/977 |
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| Summary: | Student loyalty is a crucial factor supporting the sustainability of higher education institutions. The aim of this study is to predict student loyalty using a machine learning approach, specifically the random forest algorithm. The data for this research were collected through a questionnaire that included variables such as service quality, emotional attachment, brand satisfaction, brand trust, and socio-economic conditions, distributed to 107 students in Palembang. The resulting dataset was processed through preprocessing, model training, and performance evaluation, employing metrics such as accuracy, precision, recall, and F1-score. The analysis using the random forest algorithm achieved an accuracy of 90.9%. These findings are expected to provide valuable insights for higher education institutions in developing more effective strategies to enhance student loyalty. |
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| ISSN: | 2656-5935 2656-4882 |