<![CDATA[Typhoid fever is an infectious disease caused by Salmonella typhi bacteria. Transmission of typhoid fever can occur through fecal and oral consumption of contaminated food and beverages, irregular eating patterns and lack of cleanliness in food processing sites . Symptoms in patients are analyzed by a doctor with an examination to get a diagnosis. Diagnosis of typhoid fever in patients in order to be handled quickly one of the actions that can be done by developing a system of symptoms of typhoid fever. The system was formed with a classification model from data mining techniques to diagnose typhoid fever in patients. Classification process in solving the problem of diagnosis of patients with symptoms of typhoid fever using the K-Nearest Neighbor (KNN) method. Based on the implementation and testing of the system with K-Nearest Neighbor algorithm to obtain conclusions in the analysis of each patient's symptoms in the test with the system, can provide results of diagnosis of typhoid fever in patients based on testing with training data. Analysis of the highest accuracy of K-Nearest Neighbor algorithm evaluation of 20 testing data and 10 training data contained in K=9 at 75%, recall at 66.67%, and precission 75%.]]>
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