Abstract
Chili is one of the most essential horticultural plants in Indonesia. In addition to the lack of supply of plants, the price of chili on the market has increased dramatically. The shortage is affected by unpredictable climate changes, which have to result in many chili plants suffering from crop failure. It was because the disease infects chili plants so that harvests are decreased. This work would incorporate Deep Learning for image processing in Disease Detection Systems. This disease detection method will be used to help users, in particular chili farmers, identify whether or not the leaves of their chili plants are contaminated with the disease. This system would take a picture of chili leaf using a Raspberry Pi camera and implement image processing on the chili leaf image to collect valuable information on the image to find out whether or not the chili leaf is contaminated with the disease. The purpose of this research is to make a desktop application for a disease detection system that has the ability to detect whether or not a chili leaf is infected by several diseases, display the condition of the chili leaves, display the type of disease that infects the chili leaves (if any), and provide a percentage probability of the system in detecting the image of the chili leaves correctly (whether it is healthy chili leaves or sick chili leaves). The system reaches 100 percent accuracy with good brightness and distance less than 1 meter, while the
system reaches 68.8 percent accuracy with poor brightness and distance greater than or equal to 100 percent.