<![CDATA[Skin diseases are common health issues in cats that can diminish their quality of life if not addressed early. Limited access to veterinarians makes it difficult for many cat owners to initially identify the diseases affecting their pets. Early diagnosis is challenging because many skin diseases present overlapping symptoms, making it hard for owners to distinguish between conditions without professional veterinary assistance. Therefore, this study aims to develop an expert system for the early diagnosis of these conditions using the Case-Based Reasoning (CBR) method. The system's knowledge base was constructed from a collection of 14 disease types and 36 symptoms, derived from a literature review and validated by experts. To address symptom overlap, the CBR method was implemented by calculating the similarity level between a new case and the existing case base using symptom weighting; this allows the system to differentiate between potential diseases based on similarity scores, even when multiple diseases share the same symptoms. The system then selects the case with the highest similarity score as the preliminary diagnosis. The system was developed using the Python programming language and an SQLite database. Key features include symptom selection, a diagnostic process, disease information, and the ability to generate reports in PDF format. Functional accuracy testing conducted on 14 test cases showed that 13 cases were correctly diagnosed against reference data, resulting in a functional accuracy rate of 92.85% and an average similarity score of 77.33%. The study contributes by optimizing symptom weighting within the CBR algorithm to resolve the issue of overlapping disease symptoms and by providing an integrated system that delivers disease information, care tips, similarity scores, and diagnostic reports. The results demonstrate that the CBR method is a viable approach for the early diagnosis of feline skin diseases and can serve as a helpful resource for cat owners to gather information before seeking further veterinary consultation.]]>
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