Fitria Adyati Mardha, . (2023) SISTEM PAKAR UNTUK DIAGNOSIS PENYAKIT PERNAPASAN PADA KUCING. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Cats are the most common pet in Indonesia with a cat ownership rate of 47% (Rakuten Insight, 2021). Cat owners need to know and recognize the signs and symptoms of the disease that often occur in cats, especially respiratory problems and diseases. Although vaccines in cats can significantly reduce the incidence of respiratory diseases, they do not eliminate the infectious disease pathogens. During the COVID-19 pandemic, it was necessary to adjust health consultations that could reduce the transmission of COVID-19, which is the contactless method. In animal health, there is an online consultation through WhatsApp platform between veterinarians and cat owners. Cat owners manually type every symptom experienced by the cat. However, there are several shortcomings in the online consultation, including that the symptoms described by the cat owner are unclear, so that the diagnosis data is lacking and the consultation fee is quite expensive. Based on the problems that have been mentioned, the purpose of this study is to create an expert system for diagnosing respiratory diseases in cats using the Certainty Factor method. The result of this study is the availability of an expert system that can be used to diagnose respiratory diseases in cats.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1910511006] [Pembimbing: Ria Astriratma] [Penguji 1: Bambang Saras Yulistiawan] [Penguji 2: Bayu Hananto] |
| Uncontrolled Keywords: | cat, respiratory disease, certainty factor, expert system |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Fitria Adyati Mardha |
| Date Deposited: | 01 Aug 2023 04:43 |
| Last Modified: | 01 Aug 2023 04:43 |
| URI: | http://repository.upnvj.ac.id/id/eprint/24483 |
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