Student Dropout Prediction Using Random Forest and XGBoost Method
Background: The increasing dropout rate in Indonesia poses significant challenges to the education system, particularly as students advance through higher education levels. Predicting student attrition accurately can help institutions implement timely interventions to improve retention. Objective:...
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| Principais autores: | , , |
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| Format: | Artigo |
| Jezik: | Inglês |
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Universitas Nusantara PGRI Kediri
2025-02-01
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| Serija: | Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi |
| Teme: | |
| Online dostop: | https://ojs.unpkediri.ac.id/index.php/intensif/article/view/21191 |
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