Published: 2026-04-01
Expert System for Identifying Hardware Damage Using Naïve Bayes Method (Case Study: Computer Laboratory of Sepuluh Nopember University Papua)
DOI: 10.35870/ijsecs.v6i1.5400
Isaac Samon Sabra, Heru Sutejo, Ajenkris Yanto Kungkung
- Isaac Samon Sabra: Universitas Sepuluh Nopember Papua
- Heru Sutejo: Universitas Sepuluh Nopember Papua
- Ajenkris Yanto Kungkung: Universitas Sepuluh Nopember Papua
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Abstract
This research aims to design and implement an expert system based on the Naïve Bayes method to identify computer hardware failures in the Computer Laboratory of Universitas Sepuluh Nopember Papua. The laboratory operates approximately 40 computer units used daily by students across multiple study programs, yet is supported by only three technicians — a gap that frequently delays repairs and disrupts practical sessions. The system draws on a knowledge base covering 15 hardware failure categories and 11 observable symptoms, including failures in processors, memory/RAM, storage devices (HDD/SSD), and peripheral components such as keyboards, mice, and monitors. Development followed the Waterfall model, system design was documented using UML, the application was built with CodeIgniter, and evaluation was conducted through accuracy testing against expert diagnoses. Testing on 20 cases yielded a 75% accuracy rate, demonstrating that the system is capable of supporting technicians in accelerating the troubleshooting process, reducing dependence on manual inspection, and sustaining the quality of laboratory practice sessions for students
Keywords
Expert System; Naïve Bayes; Hardware Failure; Diagnosis; CodeIgniter
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Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 6 No. 1 (2026)
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Section: Articles
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Published: 2026-04-01
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License: CC BY 4.0
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Copyright: © 2026 Authors
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DOI: 10.35870/ijsecs.v6i1.5400
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Isaac Samon Sabra, Universitas Sepuluh Nopember Papua
Informatics Engineering Department, Universitas Sepuluh Nopember Papua, Jayapura City, Papua Province, Indonesia
Heru Sutejo, Universitas Sepuluh Nopember Papua
Informatics Engineering Department, Universitas Sepuluh Nopember Papua, Jayapura City, Papua Province, Indonesia
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Aldisa, R. T. (2022). Penggunaan metode certainty factor pada sistem pakar deteksi kerusakan perangkat keras (hardware) komputer di laboratorium berbasis Android. Journal of Information System Research (JOSH), 3(3), 314–323. https://doi.org/10.47065/josh.v3i3.1528
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-
-
-
-
Hanafi, M. R., Simon, J., & Wahyuni, S. (2023). Analisis Perancangan Sistem Pakar Pendeteksi Kerusakan Hardware Pada Komputer Berbasis Web Dengan Metode Naive Bayes. Warta Dharmawangsa, 17(3), 1190-1206. https://doi.org/10.46576/wdw.v17i3.3575.
-
Lisdarti, L., & Hendriansyah, R. (2024). Perancangan Sistem Informasi Surat Menyurat Berbasis Web (Studi Kasus: Dmptpsp Kabupaten Muaro Jambi). Jurnal Akademika, 16(2), 26-32. https://doi.org/10.53564/akademika.v16i2.1181.
-
Kalyzta, J., & Syafrullah, M. (2023). Sistem pakar diagnosa kerusakan komputer dengan algoritma certainty factor pada Lab ICT Budi Luhur. Skanika, 6(1), 12–21. https://doi.org/10.36080/skanika.v6i1.2996
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Kurnia, & Irfan. (2024). Sistem Pakar Diagnosis Kerusakan Pada Komputer Menggunakan Metode Certainty Factor. Journal Of Information System And Artificial Intelligence, 4(2), 98-104. https://doi.org/10.26486/jisai.v4i2.131.
-
Mailasari, M. (2023). Sistem informasi perpustakaan menggunakan metode waterfall. Jurnal Sisfokom (Sistem Informasi dan Komputer), 8(2), 207–214. https://doi.org/10.32736/sisfokom.v8i2.657
-
Ningki, C., & N. P. (2023). Implementasi aplikasi penjualan produk tradisional berbasis website menggunakan metode waterfall. Informatika: Jurnal Ilmu Komputer, 19(2), 107–114. https://doi.org/10.52958/iftk.v19i2.6149
-
Riswandi Ishak, Setiaji, Fajar Akbar, & Mahmud Safudin. (2020). Rancang bangun sistem informasi surat masuk dan surat keluar berbasis web menggunakan metode waterfall. Jurnal Indonesia Sosial Teknologi, 1(3), 198–209. https://doi.org/10.36418/jist.v1i3.33
-
Saputra, O., Fitri, I., & Handayani, E. T. E. (2022). Sistem pakar diagnosa kerusakan hardware komputer menggunakan metode forward chaining dan certainty factor berbasis website. Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), 6(2), 234–242. https://doi.org/10.35870/jtik.v6i2.416
-
Sastypratiwi, H., & Nyoto, R. D. (2020). Analisis data artikel sistem pakar menggunakan metode systematic review. JEPIN (Jurnal Edukasi dan Penelitian Informatika), 6(2), 250-257. https://doi.org/10.26418/jp.v6i2.40914.
-
Surya Pratama, H., Putri, M., Roby, M., & Tusakdiyah, S. H. (2022). Sistem pakar diagnosa kerusakan laptop atau komputer menggunakan metode forward chaining. JEKIN - Jurnal Teknik Informatika, 2(1), 16–23. https://doi.org/10.58794/jekin.v2i1.100
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-
-
Waang Bler Tuang, S., Elefri Neno, F., & Dappa Ege, E. (2024). Penerapan metode Naïve Bayes untuk diagnosa kerusakan komputer. JATI (Jurnal Mahasiswa Teknik Informatika), 7(4), 2636–2640. https://doi.org/10.36040/jati.v7i4.7710
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