An investigation into student performance prediction using regularized logistic regression

• Main Authors: Kurniadi, Felix Indra, Dewi, Meta Amalya, Murad, Dina Fitria, Rabiha, Sucianna Ghadati, Awanis, Romli
• Format: Conference or Workshop Item
• Language: English; English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/41898/1/An%20investigation%20into%20student%20performance%20prediction.pdf; http://umpir.ump.edu.my/id/eprint/41898/2/An%20investigation%20into%20student%20performance%20prediction%20using%20regularized%20logistic%20regression_ABS.pdf; http://umpir.ump.edu.my/id/eprint/41898/; https://doi.org/10.1109/ICCED60214.2023.10425782

The problem of university dropout poses a significant challenge to education systems worldwide, affecting administrators, teachers, and students. Early identification and intervention strategies are crucial for addressing this issue. In addition, advances in machine learning have paved the way for m...