BARAPUTRI, JENNIE NADIA (2025) EXPERT SYSTEM FOR CATTLE DISEASE DIAGNOSIS USING THE FUZZY TSUKAMOTO METHOD (Case Study: Bengkel Sapi Kalijeruk). Tugas Akhir thesis, Informatics.
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Abstract
Cattle are among the most widely farmed animals in Indonesia, yet diseases affecting them remain a major challenge that can impact productivity and overall animal welfare. To address this issue, there is a critical need for accurate disease detection and diagnostic systems that can reduce the risk of disease transmission and accelerate treatment efforts. This study develops an expert system utilizing the Fuzzy Tsukamoto method, chosen for its effectiveness in handling uncertainty in clinical symptom data. The diagnostic process in the system comprises five key stages: data collection of symptoms and disease characteristics, data fuzzification, rule base formulation, fuzzy inference processing, and defuzzification. The system is designed to accept various symptom and characteristic inputs along with diagnostic rules to facilitate automated disease identification. Based on the fuzzy inference and defuzzification processes, the system successfully diagnosed Herpes and Mastitis with a 90% severity level, both categorized as “Severe.” Keywords: Fuzzy Tsukamoto, Fuzzy Logic, Cattle Disease, Livestock, Expert System.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 19 Jul 2025 02:06 |
| Last Modified: | 19 Jul 2025 02:06 |
| URI: | http://eprints.uty.ac.id/id/eprint/18278 |
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