Klasifikasi Penyakit Daun Apel Menggunakan Ekstraksi Fitur Warna RGB - Nurul Mudhofar; Soffiana Agustin (Asosiasi Riset Teknik Elektro dan Informatika Indonesia, 2024)
This research designs a system to classify apple leaf diseases using RGB (red, green and blue) color feature extraction. The essence of this research is to design a system to recognize and determine disease on apple leaves based on RGB color features using the Matlab 2024 application. The data in this research uses apple leaf images from kaggle.com, which are then cropped and adjusted to the image shape and precision in the leaf image. , Increasing the contrast of the cropped image and converting it to a grayscale image, Determining the threshold for binarization and converting the grayscale image to a binary image, Detection of green, yellow, and black/gray pixels based on RGB values ​​and calculating the proportion of each color, Detection of pixels scab by filtering out black/grey pixels that do not include green or yellow pixels Classification of leaves based on the proportion of detected colors. With the method that has been passed and uses apple leaf data, namely Healthy, Rust and Scab, each data contains 20 images with a total of 60 images and the level of accuracy is determined using the labeling method for each data and reaches the final result with an accuracy level of 86, 6667% which has a fairly accurate meaning