Analysis of Emotional and Behavioral Data of Students Experiencing Self-blaming and Exhaustion Using Decision Tree and Random Forest Methods (Case Study: SMKN 1 Sei Rampah)
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Abstract
Self-blaming and emotional exhaustion are key risk indicators for reduced engagement and well-being among students. This study applies interpretable (Decision Tree) and ensemble (Random Forest) classifiers to identify four risk groups: normal, self-blaming only, exhaustion only, and overlap (both). Using questionnaire-based emotional and behavioral indicators (Likert 1–5), the workflow follows CRISP-DM with preprocessing, stratified 80/20 split, class-imbalance handling, and evaluation using accuracy and macro/weighted F1. Results show low overlap prevalence but clinically meaningful high-risk subgroup. Random Forest achieves higher overall performance, while Decision Tree provides actionable rules for school counseling.
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How to Cite
Siti Mentari, & Muhammad Irfan Syarif. (2026). Analysis of Emotional and Behavioral Data of Students Experiencing Self-blaming and Exhaustion Using Decision Tree and Random Forest Methods (Case Study: SMKN 1 Sei Rampah). Instal : Jurnal Komputer, 18(02), 143–150. https://doi.org/10.54209/jurnalinstall.v18i02.497
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[4] J. Homepage, A. Adinegara, and S. Widodo, “MALCOM: Indonesian Journal of Machine Learning and Computer Science Prediction of Academic Burnout in College Students: A Comparative Analysis of Support Vector Machine and Random Forest Algorithms Prediksi Academic Burnout pada Mahasiswa: Analisis Komparatif Algoritma Support Vector Machine dan Random Forest,” vol. 5, pp. 1367–1376, 2025, doi: 10.57152/malcom.v5i4.2283.
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[6] D. Apriandi, R. M. Sari, and M. I. Sarif, "Clustering Analysis to Determine Outstanding Students at Private Vocational School TI Panca Dharma Stungkit Using the K-Means Method," Journal of Minfo Polgan, vol. 13, no. 1, pp. 1117–1129, Aug. 2024, doi: 10.33395/jmp.v13i1.13959.
[7] E. Hariyanto, A. Apriandi, and P. Computer System Studies, Faculty of Science and Technology, "Interactive Learning Application for Introduction to Healthy Lifestyle for Elementary Schools at Panca BudiElementarySchool,Medan.”[Online].Available: www.ijecom.org
[8] A. Rizka, R. E. Putri, and Y. Yusman, "Journal of Multi-Disciplinary Community Service Knowledge Training Introduction and Use of Decision Support System for College Department for Vocational School (STM) Students of Panca Budi Medan." [Online].Available: https://jurnal.itscience.org/index.php/jpmasdi
[9] R. M. Sari, A. Rizka, N. A. Putri, and A. Efriana, "The Application of Data Mining for Stunting Analysis in Toddlers," Journal of Minfo Polgan, vol. 13, no. 2, pp. 1717–1728, Nov. 2024, doi: 10.33395/jmp.v13i2.14218.
[10] ( Study, K. Junior High School, A. L. Medan, M. M. Pratama, F. Izhari, and A. Akbar, "Design and Construction of a Website-Based New Student Admission Information System," Journal of Minfo Polgan, vol. 13, no. 2, 2024, doi: 10.33395/jmp.v13i2.14073.
[11] Haryanto, H., Sarif, M. I., & Hardinata, R. S. (2024). Application of Data Mining to Analyze the Best Suppliers..
[12] A. I. Zalukhu, M. Iqbal, and D. Nasution, "ANALYSIS OF DATA MINING IN STOCK INVENTORY MANAGEMENT WITH RANDOM FOREST AND A PRIORI ALGORITHMS (CASE STUDY: TOKO CERIA BABYSHOP)," 2025. [Online].Available: http://jurnal.goretanpena.com/index.php/JSSR
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