Salsabila, Fannisa Tiara (2023) PENERAPAN FUZZY K-NEAREST NEIGHBOR UNTUK DIAGNOSA PENYAKIT KULIT PADA KUCING. Skripsi (S1) thesis, Universitas Muhammadiyah Ponorogo.
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Abstract
Cats are popular animals that are often encountered and kept by human. However, cats are animals that are easily attacked bacteria, viruses, or parasites that are the source of disease. One of which is skin disease. There are various kinds of skin diseases that attack cats similar symptoms that are difficult to identify, for example fur loss and scratching body. This causes commoner, especially cat owners difficulty in determining the disease suffered by his pet. Errors in handling or treating the disease can exacerbate cat's condition. If the skin disease has attacked 40% of the body, then cats can develop secondary infections. Expert systems can be applied to this case as a tool for diagnosing cat based skin diseases input in the form of symptoms by the cat owner. The method used is Fuzzy K-Nearest Neighbor. The system built based on the website uses PHP programming language and utilizes the MySQL database. This research uses 15 symptom data and 5 disease data. This research produces the highest accuracy rate is 93.3% and the highest precision level is 95%.
| Item Type: | Thesis (Skripsi (S1)) |
|---|---|
| Uncontrolled Keywords: | Fuzzy K-Nearest Neighbor, Klasifikasi, Penyakit Kulit Kucing |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering |
| Depositing User: | ft . userft |
| Date Deposited: | 04 Sep 2023 04:38 |
| Last Modified: | 04 Sep 2023 04:38 |
| URI: | http://eprints.umpo.ac.id/id/eprint/12314 |
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