Application of Naïve Bayes Method for Student Performance Classification

Riza Akhsani Setyo Prayoga, Rizky Basatha, Muhammad Sonhaji Akbar, Ersha Aisyah Elfaiz, Cendra Devayana Putra

Abstract


In every school, students exhibit varying levels of performance, influenced by several factors such as parental support and involvement, participation in extracurricular activities, motivation levels, internet access for learning, teacher quality, peer influence, and learning difficulties. This study aims to classify student performance to identify those who may need additional support for improvement. The classification method employed in this research is the Naïve Bayes algorithm. The results indicate that the trained model successfully classified 25 out of 30 tested data points. The evaluation metrics achieved include a precision of 100%, recall of 80%, specificity of 100%, accuracy of 83%, and an F1-score of 89%.

Full Text:

PDF

References


W. Fadri, “Klasifikasi Penyakit Hati dengan menggunakan Metode Naive Bayes,” Jurnal Informasi dan Teknologi, vol. 5, no. 1, pp. 32–37, 2023, doi: 10.37034/jidt.v5i1.230.

I. Hidayah, G. Putu, W. Wedashwara, and A. Zubaidi, “Sistem Monitoring Kondisi Kesehatan Sebelum dan Sesudah Olahraga menggunakan Pulse Sensor dan Sensor DS18B20 dengan Metode Naive Bayes,” J-COSINE, vol. 06, no. 01, pp. 20–29, 2022, doi: https://doi.org/10.29303/jcosine.v7i2.298.

B. Delvika, S. Nurhidayarnis, P. D. Rinada, N. Abror, and A. Hidayat, “Comparison of Classification Between Naive Bayes and K-Nearest Neighbor on Diabetes Risk in Pregnant Women,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 02, no. 02, pp. 68–75, 2022, doi: https://doi.org/10.57152/malcom.v2i2.432.

A. J. Susilo, K. K. Kustanto, and D. Remawati, “Implementasi Naïve Bayes dalam Pemilihan Jenis Bahan Pembuatan Meja,” Jurnal Ilmiah SINUS, vol. 21, no. 1, p. 39, Jan. 2023, doi: 10.30646/sinus.v21i1.674.

B. A. Maulana, M. J. Fahmi, A. M. Imran, and N. Hidayati, “Analisis Sentimen terhadap Aplikasi Pluang menggunakan Algoritma Naive Bayes dan Support Vector Machine (SVM),” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 4, no. 2, pp. 375–384, Feb. 2024, doi: 10.57152/malcom.v4i2.1206.

N. K. T. A. Saputri, I. G. A. Gunadi, and I. M. G. Sunarya, “Analisis Sentimen Pelayanan Daring di Fakultas Teknik dan Kejuruan Universitas Pendidikan Ganesha menggunakan Algoritma Naïve Bayes dan LSTM,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 4, no. 3, pp. 1120–1129, Jul. 2024, doi: 10.57152/malcom.v4i3.1336.

M. M. Alfani and Q. A’yun, “Analisis Sentimen Pasca Pertandingan Sepak Bola Indonesia Melawan Argentina pada Unggahan Media Sosial Twitter menggunakan Metode Multinomial Naïve Bayes dan Gaussian Naïve Bayes,” JASIE Jurnal Aplikasi Sistem Informasi dan Elektronika, vol. 05, no. 03, pp. 65–77, 2023, doi: http://dx.doi.org/10.32528/jasie.v5i2.22315.

R. A. Fauzi, I. Cholissodin, and B. Rahayudi, “Pemanfaatan Spark untuk Analisis Sentimen mengenai Netralitas Berita dalam membahas Pemilu Presiden 2019 menggunakan Metode Naïve Bayes Classifier,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 5, no. 3, pp. 1070–1077, 2021, [Online]. Available: http://j-ptiik.ub.ac.id

A. Putri, C. S. Hardiana, E. Novfuja, F. T. P. Siregar, Y. Fatma, and R. Wahyuni, “Comparison of K-NN, Naive Bayes and SVM Algorithms for Final-Year Student Graduation Prediction,” Institut RiMALCOM: Indonesian Journal of Machine Learning and Computer Science Journal, vol. 3, no. 1, pp. 20–26, 2023, doi: https://doi.org/10.57152/malcom.v3i1.610.

I. M. A. A. D. Putra, I. M. G. Sunarya, and I. G. A. Gunadi, “Perbandingan Algoritma Naive Bayes berbasis Feature Selection Gain Ratio dengan Naive Bayes Kovensional dalam Prediksi Komplikasi Hipertensi,” JTIM : Jurnal Teknologi Informasi dan Multimedia, vol. 06, no. 01, pp. 37–49, Apr. 2024, doi: 10.35746/jtim.v6i1.488.

A. S. Biyantoro and B. Prasetiyo, “Application of Decision Tree for Health Status Classification, Compared to KNN and Naive Bayes,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 04, no. 01, pp. 47–55, 2024, doi: https://doi.org/10.57152/ijirse.v4i1.1342.

M. A. Mujahid and M. Syafrullah, “Implementasi Algoritma Naïve Bayes Clasifier untuk mengelompokkan Naskah Berita Pendidikan dan Berita Covid-19,” KRESNA: Jurnal Riset dan Pengabdian Masyarakat, vol. 1, no. 1, pp. 34–43, 2021, doi: https://doi.org/10.36080/jk.v1i1.2.

E. F. Alamsyah and and N. Ratama, “Aplikasis Sistem Pakar Diagnosa Penyakit Balita berbasis Web menggunakan Metode Naive Bayes (Studi Kasus: Puskesmas Setu),” JORAPI : Journal of Research and Publication Innovation, vol. 1, no. 2, 2023.

N. C. Agustina, D. H. Citra, W. Purnama, C. Nisa, and A. R. Kurnia, “The Implementation of Naïve Bayes Algorithm for Sentiment Analysis of Shopee Reviews on Google Play Store,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 02, no. 01, pp. 47–54, 2022, doi: https://doi.org/10.57152/malcom.v2i1.195.

N. Semuel and A. A. Pekuwali, “Pattern Recognition of Doctor’s Prescription Handwriting using the Naïve Bayes Classifier Method at Puskesmas Kambaniru,” MALCOM: Indonesian Journal of Machine Learning and Computer Science , vol. 02, no. 01, pp. 55–61, 2022, doi: https://doi.org/10.57152/malcom.v2i1.174.

Nurdin, L. Jama, T. Z. Magnus, R. Priskila, and V. H. Pranatawijaya, “Analisis Sentimen Dampak Artificial Intelligence (AI) untuk Pendidikan pada X menggunakan Naïve Bayes,” Jurnal Informatika Upgris, vol. 10, no. 1, p. 15, 2024, doi: https://doi.org/10.26877/jiu.v10i1.18867.

W. Aliman, “Implementasi Metode Naïve Bayes untuk menentukan Persetujuan Pemberian Beasiswa Penuh pada Penerimaan Mahasiswa Baru di Institusi Pendidikan X,” Media Informatika, vol. 21, no. 03, 2022, doi: https://doi.org/10.37595/mediainfo.v22i1.91.

M. B. A. Darmawan, F. Dewanta, and S. Astuti, “Analisis Perbandingan Algoritma Decision Tree, Random Forest, dan Naïve Bayes untuk Prediksi Banjir di Desa Dayeuhkolot,” TELKA, vol. 9, no. 1, pp. 52–61, 2023, doi: http://dx.doi.org/10.15575/telka.v9n1.52-61.




DOI: https://doi.org/10.32520/stmsi.v14i2.4852

Article Metrics

Abstract view : 155 times
PDF - 71 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.