A Random Forest-Based Predictive Model for Student Academic Performance: A Case Study in Indonesian Public High Schools
DOI:
https://doi.org/10.30871/jaic.v9i3.9460Keywords:
Achievement Accuracy, Entropy, Education, PredictionAbstract
The rapid advancement of information technology has transformed education by providing tools to accurately predict students' academic performance. This study aims to develop a system for predicting academic achievement using the Random Forest algorithm, with a case study at SMAN 1 Aceh Barat Daya and SMAN 3 Aceh Barat Daya. Data from 632 student report cards for grades X and XI in the second semester of the 2023/2024 academic year were used, covering subjects such as Mathematics, Indonesian Language, and others, divided into 80% training data (506 samples) and 20% test data (136 samples). The research methodology involved data preprocessing, training the Random Forest model using entropy and information gain to construct decision trees, and performance evaluation using metrics such as accuracy, precision, and recall. The implementation resulted in a web-based application using Python and Flask, featuring an interactive interface and decision tree visualization. Testing on 136 test samples achieved an accuracy of 87.40%, with 111 correct predictions, 16 false positives, and 0 false negatives, demonstrating the model's reliability in identifying high-achieving students without missing potential. This research is expected to assist schools in identifying outstanding students, making data-driven decisions, and designing more effective educational strategies.
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[1] S. Ujud, T. D. Nur, Y. Yusuf, N. Saibi, and M. R. Ramli, “Penerapan Model Pembelajaran Discovery Learning Untuk Meningkatkan Hasil Belajar Siswa Sma Negeri 10 Kota Ternate Kelas X Pada Materi Pencemaran Lingkungan,” J. Bioedukasi, vol. 6, no. 2, pp. 337–347, 2023, doi: 10.33387/bioedu.v6i2.7305.
[2] W. Delfiana, “Pemanfaatan Perpustakaan Sekolah Oleh Guru Di SMA Negeri 1 Aceh Barat Daya,” 2022.
[3] F. Mu’Alim and R. Hiday, “Implementasi Metode Random Forest Untuk Penjurusan Siswa Di Madrasah Aliyah Negeri Sintang,” Jupiter, vol. 14, no. 1. pp. 116–125, 2022. [Online]. Available: https://www.neliti.com/publications/441871/implementasi-metode-random-forest-untuk-penjurusan-siswa-di-madrasah-aliyah-nege#cite
[4] G. A. Sandag, “Prediksi Rating Aplikasi App Store Menggunakan Algoritma Random Forest,” CogITo Smart J., vol. 6, no. 2, pp. 167–178, 2020, doi: 10.31154/cogito.v6i2.270.167-178.
[5] J. Nasir, “Penerapan Data Mining Clustering Dalam Mengelompokan Buku Dengan Metode K-Means,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 11, no. 2, pp. 690–703, 2021, doi: 10.24176/simet.v11i2.5482.
[6] A. Primajaya and B. N. Sari, “Random Forest Algorithm for Prediction of Precipitation,” Indones. J. Artif. Intell. Data Min., vol. 1, no. 1, p. 27, 2018, doi: 10.24014/ijaidm.v1i1.4903.
[7] Warjiyono, A. Nur Rais, I. Alfarobi, S. Wira Hadi, and W. Kurniawan, “Analisa Prediksi Harga Jual Rumah Menggunakan Algoritma Random Forest Machine Learning,” JURSISTEKNI (Jurnal Sist. Inf. dan Teknol. Informasi), vol. 6, no. 2, pp. 416–423, 2024.
[8] S. Adiguno, Y. Syahra, and M. Yetri, “Prediksi Peningkatan Omset Penjualan Menggunakan Metode Regresi Linier Berganda,” J. Sist. Inf. Triguna Dharma (JURSI TGD), vol. 1, no. 4, p. 275, 2022, doi: 10.53513/jursi.v1i4.5331.
[9] W. A. P. Wanto Anjar, “Analisis Prediksi Indeks Harga Konsumen Berdasarkan Kelompok Kesehatan Dengan Menggunakan MWanto, A. (2019). Analisis Prediksi Indeks Harga Konsumen Berdasarkan Kelompok Kesehatan Dengan Menggunakan Metode Backpropagation. Jurnal & Penelitian Teknik Infor,” J. Penelit. Tek. Inform., vol. 2, no. 2, pp. 37–44, 2017.
[10] A. Matondang, “Pengaruh Antara Minat Dan Motivasi Dengan Prestasi Belajar,” J. Pendidik. Bhs. dan Sastra Indones., vol. 2, no. 2, pp. 24–32, 2018, doi: https://doi.org/10.30743/bahastra.v2i2.1215.
[11] A. Maritsa, U. Hanifah Salsabila, M. Wafiq, P. Rahma Anindya, and M. Azhar Ma’shum, “Pengaruh Teknologi Dalam Dunia Pendidikan,” Al-Mutharahah J. Penelit. dan Kaji. Sos. Keagamaan, vol. 18, no. 2, pp. 91–100, 2021, doi: 10.46781/al-mutharahah.v18i2.303.
[12] I. Sekolah, “Data Pokok Pendidikan ( DAPODIK ) SMA NEGERI 1 ACEH BARAT DAYA,” pp. 24–26, 2025.
[13] W. Delfiana, “Pemanfaatan Perpustakaan Sekolah Oleh Guru Di SMA Negeri 1 Aceh Barat Daya,” 2022, [Online]. Available: https://repository.ar-raniry.ac.id/id/eprint/20495/%0Ahttps://repository.ar-raniry.ac.id/id/eprint/20495/1/Winda Delfiana%2C 160503004%2C FAH%2C IP.pdf
[14] B. Yogyakarta, “ようこそ ！ Selamat Datang !,” vol. 0022, no. April, p. 2024, 2009.
[15] Y. Ulfa, “Penerapan model pembelajaran Teams Games Tournament (TGT) terhadap kemampuan pemahaman konsep siswa di SMA Negeri 3 ABDYA,” pp. 97–98, 2021.
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