<![CDATA[Corn plant still ranks second as a staple food in Indonesia today. Limited knowledge and lack of understanding regarding the identification and handling of maize disease often result in less than optimal growth of the maize plant. If corn disease attacks when the maize is still young but the farmers are too late to control it, it is likely that it will have a bad impact on unsatisfactory yields and even result in crop failure. Given these problems, a system that has the expertise to diagnose diseases in corn is needed, which can process problems, accelerate and facilitate early detection of the risk of several diseases in corn plants. The method used to calculate the probability in the process of detecting the chance of emergence of the risk level of several diseases in corn is Case Base Reasoning using the java programming language, xml and using the Android-based MySQL database. The results of the system experiment carried out resulted in a rapid diagnosis with a percentage of certainty and a solution for treatment. Testing the respondent's assessment has resulted and it is concluded that the accuracy of the system based on the 30 data that has been tested can be seen that the diagnostic accuracy rate of this system reaches 83.33%. Keywords : Case Based Reasonig, Android, responden]]>
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