<![CDATA[One of the problems faced by rice farmers is crop failure due to diseases that spread without the knowledge of farmers. This situation can cause losses to farmers and reduce the supply of rice in Indonesia. This study aims to develop rice disease detection application using an Android smartphone. This study also aims to compare the quality of Android camera affects image detection. Detection is done by taking pictures, and the application will automatically detect the name of the disease and how to handle it. This app is developed using SDLC Waterfall, the Android operating system, and Tensorflow Lite. This research was conducted in 4 stages, namely data collection, model training, system implementation, and testing and analysis. Data collection is done by taking public data from Kaggle. The model training phase is carried out by training the models using Teachable Machine. System implementation is done by making applications. Finally, the testing and analysis phase are to test the application based on specified scenario and analyze the results of the test. The results of this study are expected to be able to help rice farmers quickly detect rice diseases that are starting to spread, so that diseases can be overcome early.]]>
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