<![CDATA[To diagnose eye disease in humans, it is necessary to calculate the best probability. Because the eyes are one of the most important parts of the human body that must be kept healthy. This study aims to analyze the comparison of 3 methods including: Case-Based Reasoning, Naïve Bayes and Certainty Factor methods so that it can be known which method is the best for diagnosing. After doing a comparison, for the calculation of the Case-Based Reasoning method, the probability result is 61.6%, the Naïve Bayes method is 56.36% and the Certainty Factor method is 90.4%. It can be concluded that the Certainty Factor method is the best method for diagnosing eye diseases in humans. After that, an expert system will be made using the Certainty Factor method to diagnose eye diseases in humans. An expert system is an imitation of an expert in diagnosing a disease. The purpose of this expert system is to help patients to diagnose what type of eye disease based on the symptoms they experience.]]>
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