Predicting Students Graduate on Time Using C4.5 Algorithm
Background: Facilitating an effective learning process is the goal of higher education institutions. Despite improvement in curriculum and resources, many students cannot graduate on time. Mostly, the number of students who graduate on time is lower than the number of new students enrolling to unive...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Airlangga
2021-04-01
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| Series: | Journal of Information Systems Engineering and Business Intelligence |
| Online Access: | https://e-journal.unair.ac.id/JISEBI/article/view/25182 |
| _version_ | 1811159683486973952 |
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| author | Herman Yuliansyah Rahmasari Adi Putri Imaniati Anggit Wirasto Merlinda Wibowo |
| author_facet | Herman Yuliansyah Rahmasari Adi Putri Imaniati Anggit Wirasto Merlinda Wibowo |
| author_sort | Herman Yuliansyah |
| collection | DOAJ |
| description | Background: Facilitating an effective learning process is the goal of higher education institutions. Despite improvement in curriculum and resources, many students cannot graduate on time. Mostly, the number of students who graduate on time is lower than the number of new students enrolling to universities. This could dilute the chance for students to learn effectively as the ratio between faculty members and students becomes non-ideal.
Objective: This study aims to present a prediction model for students’ on-time graduation using the C4.5 algorithm by considering four features, namely the department, GPA, English score, and age.
Methods: This research was completed in three stages: data pre-processing, data processing and performance measurement. This predicting scheme make the prediction based on the department of study, age, GPA and English proficiency.
Results: The results of this study have successfully predicted students’ graduation. This result is based on the data of students who graduated in 2008-2014. The prediction performance result achieved 90% of accuracy using 300 testing data.
Conclusion: The finding is expected to be useful for universities in administering their teaching and learning process. |
| first_indexed | 2024-04-10T05:45:18Z |
| format | Article |
| id | doaj.art-66a46b2cc3fe4dfc930421eb8477b507 |
| institution | Directory Open Access Journal |
| issn | 2598-6333 2443-2555 |
| language | English |
| last_indexed | 2024-04-10T05:45:18Z |
| publishDate | 2021-04-01 |
| publisher | Universitas Airlangga |
| record_format | Article |
| series | Journal of Information Systems Engineering and Business Intelligence |
| spelling | doaj.art-66a46b2cc3fe4dfc930421eb8477b5072023-03-06T02:56:32ZengUniversitas AirlanggaJournal of Information Systems Engineering and Business Intelligence2598-63332443-25552021-04-0171677310.20473/jisebi.7.1.67-7320624Predicting Students Graduate on Time Using C4.5 AlgorithmHerman Yuliansyah0https://orcid.org/0000-0003-2088-6956Rahmasari Adi Putri Imaniati1Anggit Wirasto2Merlinda Wibowo3https://orcid.org/0000-0002-1730-7258Universitas Ahmad DahlanUniversitas Ahmad DahlanUniversitas Harapan BangsaInstitut Teknologi Telkom PurwokertoBackground: Facilitating an effective learning process is the goal of higher education institutions. Despite improvement in curriculum and resources, many students cannot graduate on time. Mostly, the number of students who graduate on time is lower than the number of new students enrolling to universities. This could dilute the chance for students to learn effectively as the ratio between faculty members and students becomes non-ideal. Objective: This study aims to present a prediction model for students’ on-time graduation using the C4.5 algorithm by considering four features, namely the department, GPA, English score, and age. Methods: This research was completed in three stages: data pre-processing, data processing and performance measurement. This predicting scheme make the prediction based on the department of study, age, GPA and English proficiency. Results: The results of this study have successfully predicted students’ graduation. This result is based on the data of students who graduated in 2008-2014. The prediction performance result achieved 90% of accuracy using 300 testing data. Conclusion: The finding is expected to be useful for universities in administering their teaching and learning process.https://e-journal.unair.ac.id/JISEBI/article/view/25182 |
| spellingShingle | Herman Yuliansyah Rahmasari Adi Putri Imaniati Anggit Wirasto Merlinda Wibowo Predicting Students Graduate on Time Using C4.5 Algorithm Journal of Information Systems Engineering and Business Intelligence |
| title | Predicting Students Graduate on Time Using C4.5 Algorithm |
| title_full | Predicting Students Graduate on Time Using C4.5 Algorithm |
| title_fullStr | Predicting Students Graduate on Time Using C4.5 Algorithm |
| title_full_unstemmed | Predicting Students Graduate on Time Using C4.5 Algorithm |
| title_short | Predicting Students Graduate on Time Using C4.5 Algorithm |
| title_sort | predicting students graduate on time using c4 5 algorithm |
| url | https://e-journal.unair.ac.id/JISEBI/article/view/25182 |
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