<![CDATA[This study aims to compare the effectiveness of two methods, Certainty Factor (CF) and Case-Based Reasoning (CBR), in detecting Takayasu's Arteritis. Takayasu's arteritis is a complex disease with varying symptoms, giving rise to difficulties in correct diagnosis. The main aim of this study was to evaluate their performance in the context of such complex disease detection. The main problem faced is the uncertainty in assessing the level of certainty of diagnosis based on symptoms that vary between patients. The CF method uses the confidence factor principle to measure the level of certainty in a diagnosis, while CBR uses knowledge from previous cases to design a diagnosis for new cases. This study uses a dataset that includes information on symptoms and patient history related to Takayasu's Arteritis. The experimental process involves implementing both methods on the dataset, with results including evaluation of accuracy, sensitivity, and specificity levels. The research results highlight differences in the performance of Certainty Factor and Case-Based Reasoning in detecting Takayasu's Arteritis, providing in-depth insight into the advantages and disadvantages of each method. It is hoped that this understanding can help develop a more efficient and accurate detection system to overcome the complexity of diagnosing Takayasu's Arteritis. The percentage results from the two approaches used in diagnosing Arteritis Takayasu disease have been presented. The Certainty Factor Method indicates a confidence level of 94%, while the Case Based Reasoning Method shows a similarity level of 54%. This significant difference reflects the superiority of the Certainty Factor Method in providing a higher level of confidence in diagnosing this disease compared to the Case Based Reasoning approach.]]>
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