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All Journal JOIV : International Journal on Informatics Visualization
Muhammad Insan Al-Amin
UIN Sunan Gunung Djati Bandung, 40614, Indonesia
Computer Science & IT

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Exploring Classification Algorithms for Detecting Learning Loss in Islamic Religious Education: A Comparative Study Sapdi, Rohmat Mulyana; Maylawati, Dian Sa'adillah; Ramdania, Diena Rauda; Budiman, Ichsan; Al-Amin, Muhammad Insan; Fuadi, Mi'raj
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.1823

Abstract

This study investigates the detection of learning loss in Islamic religious education subjects in Indonesia. Focusing on the effectiveness of multiple classification algorithms, the research assesses learning loss across literacy, numeracy, writing, and science domains. While education traditionally involves knowledge transmission, it also seeks to instill values. Given Indonesia's predominantly Islamic demographic, Islamic Religious Education (IRE) is pivotal in disseminating moral and cultural values, encompassing teachings from the Koran, Hadith, Aqedah, morality, Fiqh, and Islamic history. The study's central aim is to discern learning loss in IRE in Islamic schools, utilizing the Gradient Boosting Classifier as its primary analytical tool. Various classification algorithms, including the Cat Boost Classifier, Light Gradient Boosting Machine, Extreme Gradient Boosting, and others, were tested. The study engaged a sample of 38,326 Islamic Elementary school students, 29,350 Islamic Junior High school students, and 13,474 Islamic High school students across Indonesia. The findings revealed that the Light Gradient Boosting Machine was the most effective model for Islamic Elementary and High school data, while the Cat Boost Classifier excelled for Islamic Junior High school data. These results highlight the extent of learning loss in IRE and offer invaluable perspectives for education stakeholders. Future studies are encouraged to further explore the root causes of this learning loss and devise specific interventions to tackle these issues effectively.
Co-Authors Diena Rauda Ramdania Ichsan Budiman Maylawati, Dian Sa'adillah Mi’raj Fuadi Rohmat Mulyana Sapdi