<![CDATA[Acute Respiratory Infection (ARI) is a major cause of morbidity (number of diseases) from various infectious diseases in the world. Bacteria, mycoplasma virus, fungi are a small part of various causes of ARI disease. Based on the severity, ARI disease can also be divided into 2, namely mild ARI and severe ARI. The low level of public information about knowledge about diseases, especially ARI, is an important factor why the mortality rate due to ARI is very high. In addition, sufficient numbers of medical personnel are needed to help communities in certain areas of Indonesia to be able to cope with ARI disease and get to know more widely ARI disease. Therefore, expert systems are expected to be a solution or rapid treatment and in helping diagnose ARI. This study also uses the Tsukamoto fuzzy method in the process of calculation and implementation. The application of fuzzy tsukamoto method of diagnosis of ARI disease, applying input from symptoms of ARI that appear as a reference for the diagnosis of disease. In the system, experts provide 5 symptoms and 2 types of ARI disease. Accuracy testing is done by testing the accuracy of 60 training data obtained from experts and there are 53 of the 60 data that match the results released by the system with expert results. The accuracy value obtained is 88.33%.]]>
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