Setiawan, M. Tegar (2025) Klasifikasi Penentuan Penyakit pada Sapi Berdasarkan Gejala Menggunakan Algoritma ID3. Other thesis, Universitas Islam Riau.

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Abstract

Cattle farming plays a crucial role in the agricultural sector and food security. However, the success of livestock management is often hampered by various diseases affecting cattle. Early detection of diseases is essential to prevent economic losses and livestock mortality. This study aims to develop a disease classification system for cattle based on observed clinical symptoms, using the Iterative Dichotomiser 3 (ID3) algorithm. The ID3 algorithm is chosen for its ability to generate decision trees based on the highest information gain, making it efficient and accurate in data classification. The data used includes common symptoms such as diarrhea, fever, dull fur, anorexia, anestrus, and excessive saliva. The research stages include data collection, pre-processing, model development, and performance evaluation using accuracy, precision, recall, and f1-score metrics. The testing results show that the ID3 algorithm can classify cattle diseases with a relatively high accuracy. This system is expected to assist farmers and related agencies in performing early and accurate diagnoses, enabling more timely treatment.

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