Klasifikasi Motif Songket Palembang menggunakan Support Vector Machine berdasarkan Histogram of Oriented Gradients - Yohannes, Yohannes; Al Rivan, Muhammad Ezar; Devella, Siska; Meiriyama, Meiriyama (LPPM STT Terpadu Nurul Fikri, 2023)
Songket Palembang is one of the intangible cultural heritages with the domain of traditional craftsmanship and crafts. Songket Palembang has several motifs, including Chinese Flowers, Cantik Manis, and Pulir. Preservation efforts are carried out by providing an understanding of Palembang Songket patterns. This study classified Palembang Songket patterns based on shape features using the Histogram of Oriented Gradient (HOG) method. Based on the test results of 45 test data images, the HOG method can become a feature in the image classification of Palembang Songket patterns, namely Chinese Flowers, Cantik Manis, and Pulir. The Support Vector Machine (SVM) method is a classification method that can recognize Palembang Songket patterns with RBF, Linear, and Polynomial kernels. The results showed that the RBF kernel was the best kernel that produced an average accuracy value of 88.1%, a precision of 84.1%, a recall of 82.2%, and an f1-score of 82.6%, and the three Palembang Songket patterns tested, it was found that the Palembang Songket patterns that were easiest to classify well were the Cantik Manis patterns for all types of SVM kernels.