<![CDATA[Fever is one of the health problems that disrupt everyone's productivity, even it can cause death and remain a health problem in Indonesia. There are several types of fever that needs to be wary, it includes dengue, malaria and typhoid. These three diseases have similar symptoms, so many medical personnel and doctors internship often make mistakes in diagnosing the disease. Therefore, an expert system is required to resolve the issue. The method used to support the expert system is K-Nearest Neighbor - Certainty Factor which is a merger of two methods in which the classification results of K-Nearest Neighbor to be rated certainty by a Certainty Factor method and resulting a diagnosis of the disease. In this study, the training data and test data used were 143 data. Based on test results obtained K value variation accuracy of 88.37%. On testing variations training data obtained an accuracy of 86.04%. In testing the ratio of training data and test data obtained an accuracy of 95%. In testing the variation of the number of test data obtained an accuracy of 90%. In testing the variety of test data obtained an average accuracy of 97.22%. In comparison testing method, the method k-nearest neighbor certainty factor gets an accuracy of 84.79%.]]>
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