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All Journal Media Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan
Syarip, Dodi Irawan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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COMPARISON OF RANDOM FOREST AND SUPPORT VECTOR MACHINE CLASSIFICATION METHODS FOR PREDICTING THE ACCURACY LEVEL OF MADRASAH DATA Syarip, Dodi Irawan; Notodiputro, Khairil Anwar; Sartono, Bagus
MEDIA STATISTIKA Vol 18, No 1 (2025): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.18.1.37-48

Abstract

This study aims to identify the most effective classification method for predicting the accuracy level of madrasah data with class imbalance. Two machine learning approaches were employed: Random Forest (RF) and Support Vector Machine (SVM). Based on the AUC values, it was concluded that the RF model had a slightly better performance in predicting the accuracy level of the madrasah data, with an average AUC of 62.82, compared to the SVM model, which had an average AUC of 62.33. Among all models, the highest and consistent performance was achieved by the RF model using ROSE techniques. The results of measuring variable importance showed that the predictor variables with the greatest influence in predicting the accuracy level of the madrasah data are the number of students and the student-to-teacher and staff ratio. This finding suggests that school principals and madrasah administrative staff should prioritize ensuring the completeness of student, teacher, and staff data to improve the overall reliability of madrasah data.
TREE-BASED MIXED EFFECTS MODELING OF TEACHER CERTIFICATION OUTCOMES IN MADRASAH ALIYAH: A COMPARATIVE STUDY OF GLMM TREES AND GMET Syarip, Dodi Irawan; Notodiputro, Khairil Anwar; Sartono, Bagus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1199-1214

Abstract

The Teacher Professional Education program, or “Pendidikan Profesi Guru” (PPG), is a continuing education program designed for prospective or in-service teachers to obtain a teaching certificate. PPG is a priority program of the Ministry of Religious Affairs in providing competent and professional madrasah teachers. This study is expected to identify the challenges encountered in the implementation of the Madrasah teacher certification program and provide valuable input to enhance the success rate of Madrasah Aliyah teachers in the PPG program. The main objective of this study is to find the most appropriate tree-based mixed effects model to analyze the effectiveness of PPG for Madrasah Aliyah teachers in 2022. This study applies two tree-based mixed effects modeling methods: generalized linear mixed model trees (GLMM trees) and generalized mixed effects trees (GMET). Both methods model variability across subjects as a random effect. Based on the performance indices measurement results, the GMET model shows superiority over the GLMM trees model. The GMET model has an accuracy index of 0.7653, higher than the GLMM trees model of 0.7306. Substantively, teachers of English and Indonesian Language exhibit higher probabilities of passing than those of other subjects, whereas Arabic and Islamic Cultural History have the lowest estimated probabilities of success. Analysis of the variable importance from both models indicates that teachers’ age is the most influential predictor of PPG graduation among Madrasah Aliyah teachers. Based on these findings, to improve the effectiveness of PPG implementation for madrasah Aliyah teachers, policymakers at the Ministry of Religious Affairs are advised to implement a structured coaching and mentoring program for prospective PPG participants, with a special emphasis on support for senior teachers specializing in Arabic and Islamic Cultural History.
Co-Authors Bagus Sartono