Pengenalan Motif Batik Banyuwangi Berdasarkan Fitur Grey Level Co-Occurrence Matrix

Abstract

Batik is one of Indonesia’s cultural heritages that is recognized around the world and has existed since the colonial era. Indonesia has a variety of different batik pattern in every Indonesia’s region. It causes many ordinary people and tourists to become harder to identify and recognize the existing patterns. Banyuwangi regency itself has more than 10 batik patterns, including the Gajah Oling pattern which in the oldest batik pattern. For preserving the culture and supporting the growing tourism aspect in Banyuwangi, this study developed a system for recognizing Banyuwangi batik patterns based on digital image processing. This system is built using python language and is able to recognize three classes of Banyuwangi batik patterns, such as Gajah Oling, Kopi Pecah and other Banyuwangi batik patterns. This system proposes Gray Level Co-occurrence Matrix (GLCM) as feature extraction method and k-Nearest Neighbors (kNN) as classification method. Based on the experiments that have been carried out, the optimal accuracy is 87,5% with the K parameter of kNN is 9.