• Chalifa Chazar
  • Nisa Hanum Harani
  • Andang Kurniawan


Cats are one of the most popular pets. Caring a cat, that are not enough just to be given food and drink, but their hygiene and health factors also needed special attention. Cats are susceptible to disease, even some diseases can cause negative effects on humans, for example can cause disability and miscarriage in the fetus (if this infection occurs in pregnant women). The limitations of medical personnel and knowledge in society are the one factors that cause high mortality rates in cats. Therefore, not only cat’s owner but society too need to be knowing about diseases that can attack cats. This research aims to build a capable system to provide predictions of cats’ diseases based on their symptoms. The Naïve Bayes Method can be used to produce a prediction in machine learning based on data training, using conditional probabilities as the basis. Another advantage using this method is that can provide a high level of accuracy simply by using a small amount of data training. The results of this research are a building a system that can provide predictions of cats diseases based on their symptoms, and based on the testing results this system can provide accurate results in accordance with data obtained from experts (veterinarians).

Mar 27, 2019
How to Cite
CHAZAR, Chalifa; HARANI, Nisa Hanum; KURNIAWAN, Andang. SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PADA KUCING MENGGUNAKAN METODE NAÏVE BAYES. Jurnal Teknik Informatika, [S.l.], v. 11, n. 1, p. 18-24, mar. 2019. ISSN 1979-8326. Available at: <>. Date accessed: 15 july 2019.