Deteksi Penyakit Pembibitan Pada Tanaman Durian Berdasarkan Citra Menggunakan Convolutional Neural Network - RIZKI NURFIRDAUS, MUH. IQBAL; Rafi, Muhamad; Bayu Seno Adjie (Jurnal Riset Informatika dan Teknologi Informasi, 2023)
The cultivation of durian plants in Indonesia has a high economic value, various variants make it very attractive to many people. However, limited knowledge about the disease is the reason for the low quality and price in the market. Therefore a detection system is needed that can classify the characteristics and forms of several diseases. This research is to make it easier for farmers to treat them. Using the Convolutional Neural Network (CNN) method which includes supervised learning so that it can be carried out for classification of affected parts of the durian plant and a data approach that has been trained and is variable. The purpose of this study was to determine the types of diseases found in durian plants. The results of tests that have been carried out with a classification accuracy level using CNN of 0.9233 with a repetition of 200 epochs from the process carried out get results in the form of pictures and descriptions of the types of diseases so that they can help improve quality and price.