Web-Based Expert System for Diagnosing Diseases in Medium Persian Cats

Web-Based Expert System for Diagnosing Diseases in Medium Persian Cats

Authors

  • Zidane Chesa Wardana Universitas Nusantara PGRI Kediri
  • Intan Nur Farida universitas Nusantara PGRI Kediri
  • Made Ayu Dusea Widya Dara universitas Nusantara PGRI Kediri

DOI:

https://doi.org/10.29407/noe.v6i2.20522

Keywords:

Diagnosa Penyakit Kucing, Kucing Persia Medium, Naïve Bayes, Sistem Pakar

Abstract

This research creates a web-based expert system that uses the Bayes method for diagnosing disease in Persian Medium cats. This system offers a cheaper and more effective solution for cat owners to get an early diagnosis of disease without having to go to expensive veterinary clinics. The results of calculations using the Naive Bayes method show that the largest posterior value P(P2|G2|G7|G11) is 0.0093, which is then normalized to 100%, indicating that the cat in this case may have hair ball disease. Thus, it can be concluded that the cat in this case has hair ball disease. Persian Medium cat owners can use this expert system to diagnose their cat's disease more cheaply and effectively.

References

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Fadhilah, F., Andryana, S., & Gunaryati, A. (2020). Penerapan Metode Naïve Bayes Pada Aplikasi Sistem Pakar Untuk Diagnosa Penyakit Kulit Pada Kucing. Jurnal Infomedia, 5(1), 23–30. http://e-jurnal.pnl.ac.id/index.php/infomedia/article/view/1602
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Ridho Handoko, M., & Neneng. (2021). Sistem Pakar Diagnosa Penyakit Selama Kehamilan Menggunakan Metode Naive Bayes Berbasis Web. Jurnal Teknologi dan Sistem Informasi (JTSI), 2(1), 50–58. http://jim.teknokrat.ac.id/index.php/JTSI
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Published

2023-10-26

How to Cite

Zidane Chesa Wardana, Farida, I. N., & Dara, M. A. D. W. . (2023). Web-Based Expert System for Diagnosing Diseases in Medium Persian Cats: Web-Based Expert System for Diagnosing Diseases in Medium Persian Cats. Nusantara of Engineering (NOE), 6(2), 175–182. https://doi.org/10.29407/noe.v6i2.20522

Issue

Vol. 6 No. 2 (2023): Volume 6 No 2 Tahun 2023

Section

Artikel

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