Integrasi Metode Forward Chaining dan Teorema Bayes Untuk Identifikasi Diagnosa Penyakit Kulit Pada Kucing

Authors

  • Ade Anugerah Universitas Muhammadiyah Pontianak
  • Sucipto Sucipto Universitas Muhammadiyah Pontianak
  • Syarifah Putri Agustini Alkadri Universitas Muhammadiyah Pontianak

DOI:

https://doi.org/10.37859/jf.v15i3.10288
Keywords: diagnosis, Forward Chaining, Laravel, MySQL, Cat skin disease, expert system, Bayes Theorem

Abstract

Skin diseases in cats are among the most common health issues, yet many cat owners still lack awareness of their symptoms. Limited access to veterinary services, especially in regions such as West Kalimantan, poses a significant challenge in early identification and treatment. This study aims to develop a web-based expert system capable of automatically diagnosing skin diseases in cats based on symptoms inputted by users. The system utilizes the Forward Chaining method for rule-based inference and the Bayes Theorem for probabilistic calculation to determine the likelihood of diseases. The system was built using the Laravel framework and MySQL database, based on a total of 83 case data obtained through direct interviews with veterinary experts. Testing using black-box and user acceptance methods showed that the system functions effectively and delivers accurate and informative diagnostic results. The system achieved an accuracy rate of 100% when tested on validated expert data. Therefore, this system can serve as an effective tool for cat owners to quickly and independently gain initial insights into their cat’s skin health before consulting a veterinarian.

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Published

2025-12-31

Issue

Vol. 15 No. 3 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)

Section

Articles

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Copyright (c) 2025 Ade Anugerah, Sucipto, Syarifah Putri Agustini Alkadri

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