Implementasi Metode Fuzzy K-Nearest Neighbor Untuk Klasifikasi Penyakit Tanaman Kedelai Pada Citra Daun - Yerry Anggoro; Budi Darma Setiawan; Putra Pandu Adikara (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Protein is one of essential thing to the human body, there are many source of protein and one of it is a soy which is nabati protein source. besides corn and rice, soy is the main food commodities in Indonesia. However, domestic production of soybean has not been enough to fulfil the necessity. Soybean production at the level of actual farmers could still be enhanced through technological innovation, one of that is to detect plant disease of soybeans on the leaves by the method of Fuzzy K-Nearest Neighbor and the segmentation using the method of Otsu. The image processed with the method of Otsu to separate parts that are diseased with parts that are not diseased and then do a classification by the method of Fuzzy K-Nearest Neighbor to determine leaf rust disease, Downy Mildew, and bacterial pustule. There are four tests such as test comparison data training and test data with the highest accuracy in comparison with a total of 90:10 54 training data and test data of 6 100%, testing against the values of Threshold with T = 10 generates 83,33% accuracy, testing against the values of k = 5 generates 83,33%, accuracy and testing against the values m = 2 with accuracy of 83,33%.