Identifikasi Kematangan Cabai Rawit Menggunakan Metode Momen Warna Dan SVM - Ridhovi, Zainul; Erwanto, Danang; Yanuartanti, Iska (Prodi Teknik Elektro Universitas PGRI Banyuwangi, 2025)
This study focuses on the identification of the ripeness of bird's eye chili (Capsicum annuum L.) using the color moment method and Support vector machine (SVM). Bird's eye chili holds significant economic value in the agricultural industry, but the rapid and accurate identification of ripeness remains a challenge. The color moment method is employed to extract features from images of bird's eye chili, while SVM is used for classification based on the extracted features. This research expands the use of data and optimizes SVM parameters to enhance the accuracy of identification. The results indicate that the classification model using the SVM method successfully classifies the ripeness levels of chili with an accuracy of 82%, categorized as good. Specifically, it achieved a precision of 66.67%, recall of 83.33%, and F-measure of 74.07% for the