<![CDATA[Agriculture is an activity to manage biological natural resources with the help of technology and labor. The presence of diseases in plants that suddenly inhibit plant growth is alarming to farmers. So, farmers cannot determine what conditions these plants suffer. This study will discuss the implementation of Artificial Intelligence-based plant disease detection software. At this stage, deep learning models are created using cameras matched with objects. The application development is to detect diseases in plants. The fourth step is testing. This application includes the implementation of Convolutional Neural Network and Recurrent Neural Network, which provides Artificial Intelligence architecture to diagnose plant diseases, and offer solutions to those plants from the results of research with tomato plant sample tests obtained four categories of disease Early Blight disease with a prediction of 100%, Bacterial Spots 90%, Healthy 100%, Late Blight 100% a system that can recommend health care related to crops based on images so that it can help farmers identify types of plant diseases. This application can help farmers to reduce crop failure for farmers caused by plant diseases to improve the quality of agricultural and plantation products]]>
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