Abstract

This research discusses expert system that can be used to diagnose lung disease. The research use Case Base Reasoning (CBR) method. CBR is one of method that use artificial intelligence approach (AI) and emphasizes the problem solving based on knowledege of previous cases. The cases used were obtained from the cases records of lung disease diagnosis from a pulmonary specialist doctor as much as 8 cases and provided a single new case for the calculated value of its proximity to the old case. The results of this research provide the output of the disease possibility and treatment suggestions based on the similarity of new cases with knowledge of the system. Value of proximity of 8 old cases against new cases of a patient was 0.38 for the first case data, 0.45 for the second case data, 0.56 for the third case data, 0.56 for the fourth case data, 0.72 for the fifth case data, the data is 0.93 for the sixth case, 0.52 of the seventh case data, and 0.66 to the last case data. Maximum proximity value of data obtained by the sixth case, which is 0.93, or 93%, so it can be concluded that patients diagnosed pneumococcal disease

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