Benediktus, Natanael and Oetama, Raymond Sunardi (2020) Algoritma Klasifikasi Decision Tree C5.0 untuk Memprediksi Performa Akademik Siswa. Ultimatics : Jurnal Teknik Informatika, 12 (1). pp. 14-19. ISSN 2085-4552
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Abstract
Student’s performance is often used as a benchmark and a student’s activeness is frequently used as a criteria of how well a student academically perform at school. The goal of this study is to find out whether the activeness of a student can predict their academic performance. The data used is an educational dataset is collected using a learning management system (LMS), which is a learner activity tracker tool that is connected by the internet. This data has numerical and categorical variables, so it is needed to have the right algorithm to classify data accurately and ensure data validity. In this study, the C.50 algorithm is used to test the data, where the data is divided into training data by 75% and testing data by 25%. And the result from the tested data, an accuracy of 71.667% is obtained.
| Item Type: | Article |
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| Keywords: | C5.0 Algorithm, Data Classification, Decision Tree, Student’s Performance |
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming > 005.2 Programming for Specific Computers, Algorithm, HTML, PHP, java, C++ |
| Sustainable Development Goals: | Goal 10 Reduce inequality within and among countries Goal 04. Ensure inclusive and equitable quality education and promote lifelong learning Goal 09. Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation |
| Divisions: | Faculty of Engineering & Informatics > Information System |
| Date Deposited: | 04 Apr 2023 06:59 |
| URI: | https://kc.umn.ac.id/id/eprint/25233 |
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