PENERAPAN FUZZY K-NEAREST NEIGHBOR UNTUK DIAGNOSA PENYAKIT KULIT PADA KUCING
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Institusion
Universitas Muhammadiyah Ponorogo
Author
Salsabila, Fannisa Tiara
Subject
TK Electrical engineering. Electronics Nuclear engineering
Datestamp
2023-09-04 04:38:34
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%.
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%.
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