<![CDATA[The diagnosis of Ear, Nose, and Throat (ENT) diseases often encounters difficulties in determining the level of certainty of a disease based on the symptoms experienced by the patient. The main issue in this study is how to compare the accuracy levels between the Certainty Factor and Dempster-Shafer methods in expert systems for diagnosing ENT diseases. As a solution, this research applies both methods and analyzes their computational results based on various symptoms entered by patients. The objective of this study is to identify which method is more effective in providing diagnostic certainty. The findings indicate that the Certainty Factor method produces a higher level of certainty compared to the Dempster-Shafer method — for instance, in the case of tonsillitis, achieving 94.68% compared to only 0.02% with Dempster-Shafer. Therefore, the Certainty Factor method is recommended for use in expert systems for ENT disease diagnosis. This study contributes to enhancing understanding of the application of artificial intelligence methods in the medical field, particularly in improving the accuracy of expert systems to assist healthcare professionals in diagnostic decision-making processes.]]>
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