<![CDATA[This study aims to evaluate the user experience quality and diagnostic accuracy of an Android-based expert system application developed to assist in diagnosing diseases in tilapia fish. The evaluation employed the User Experience Questionnaire (UEQ) and the Certainty Factor (CF) approach. UEQ results indicate that the application delivers a highly satisfying user experience, with the highest scores on stimulation (1.68) and attractiveness (1.60), both categorized as Excellent. These results suggest that the application provides an engaging and enjoyable interactive experience. Other dimensions such as clarity (1.34), efficiency (1.37), accuracy (1.18), and novelty (1.20) fall into the Good category, indicating the system is intuitive, functional, and reliable, though there is still room for improvement.In terms of expert system performance, the Certainty Factor method successfully delivered relevant diagnostic results. Tricodiniasis emerged as the primary diagnosis with 100% confidence based on the user's selected symptoms. However, the appearance of several other diseases with similarly high confidence scores indicates the existence of overlapping symptoms across different conditions. This highlights the importance of using probabilistic approaches to manage uncertainty in disease diagnosis. Overall, the application demonstrates strong performance in user interface design, user interaction, and expert system accuracy, making it suitable as a supporting tool for diagnosing tilapia fish diseases]]>
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