IMPLEMENTATION AND DEVELOPMENT OF THE NAÏVE BAYES METHOD IN AN EXPERT SYSTEM TO DETECT FUNCTIONAL DAMAGES IN LAPTOP HARDWARE

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Published: Dec 31, 2025
DOI: https://doi.org/10.30742/melekitjournal.v11i2.427
Keywords:
naive bayes, Expert Systems, laptop damage diagnosis, damage symptoms

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Neli Nailul Wardah
Universitas Mathla'ul Anwar Banten
Zaenal Hakim
Universitas Mathla’ul Anwar
Sulhani Sulhani
Universitas Mathla’ul Anwar

Abstract

Laptops have become one of the most essential technological devices in everyday life. With their portability and versatility, laptops have become incredibly useful tools for many people. However, like any other device, laptops can experience damage that can impact user performance and productivity. Laptop damage can be caused by various factors, both hardware and software. An expert system can help diagnose laptop damage more quickly and accurately. This research aims to develop an expert system for diagnosing laptop damage using the Naive Bayes method. The expert system is designed to identify the type of laptop damage based on symptoms experienced by users. The Naive Bayes method is used to calculate the probability of laptop damage based on existing data. The results show that the expert system can diagnose laptop damage with a high level of accuracy. This expert system can help laptop users identify damage and determine the appropriate repair actions.

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How to Cite
[1]
“IMPLEMENTATION AND DEVELOPMENT OF THE NAÏVE BAYES METHOD IN AN EXPERT SYSTEM TO DETECT FUNCTIONAL DAMAGES IN LAPTOP HARDWARE”, MelekIT, vol. 11, no. 2, pp. 125–136, Dec. 2025, doi: 10.30742/melekitjournal.v11i2.427.
Issue
Vol. 11 No. 2 (2025): Melek IT: Information Technology Journal
Section
Original Research
Creative Commons License

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

How to Cite

[1]
“IMPLEMENTATION AND DEVELOPMENT OF THE NAÏVE BAYES METHOD IN AN EXPERT SYSTEM TO DETECT FUNCTIONAL DAMAGES IN LAPTOP HARDWARE”, MelekIT, vol. 11, no. 2, pp. 125–136, Dec. 2025, doi: 10.30742/melekitjournal.v11i2.427.
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