a PREDIKSI SISWA PUTUS SEKOLAH DAN KEBERHASILAN AKADEMIK MENGGUNAKAN MACHINE LEARNING: Prediksi Siswa Putus Sekolah dan Keberhasilan Akademik

Siti Fitriana; riniyanty; rahma laila; septiano anggun pratama; chairunnisa ar lamasitudju

doi:10.33022/ijcs.v13i6.4453

Authors

Siti Fitriana Universitas Tadulako
riniyanty Department of Informatics Engineering, Faculty of Engineering, Palu, Indonesia
rahma laila Department of Informatics Engineering, Faculty of Engineering, Palu, Indonesia
septiano anggun pratama Department of Informatics Engineering, Faculty of Engineering, Palu, Indonesia
chairunnisa ar lamasitudju Department of Informatics Engineering, Faculty of Engineering, Palu, Indonesia

DOI:

https://doi.org/10.33022/ijcs.v13i6.4453

Keywords:

Prediksi siswa putus sekolah, keberhasilan akademik, machine learning di pendidikan

Abstract

In 2020-2023. The issue of high school dropouts at SMA Negeri 2 Sigi increased, causing impacts such as declining school accreditation, a decrease in the number of students, and operational aid. This research aims to build an early prediction system for student dropouts using Machine Learning (ML). In this study, data from 200 students were used. With 16 students labeled as dropout. The results showed a model accuracy of 0.942 and an area under the curve (AUC) of 0.948. the factors most influencing student droppout are average grades, meeting targets, and father’s education leve.