Classification of coastal and Inland Batik using GLCM and Canberra Distance

As an effort to preserve one of the Indonesian cultural products, this study discusses the predictions of traditional motifs. The case study is the Coastal Batik and Inland Batik. The diversity of traditional batik motifs in Indonesia began to erode due to the influx of foreign culture hence the authenticity of the traditional motifs of a particular area is not synonymous with the region of origin. As a consequent, due to many traditional Indonesian motifs, it is difficult to recognize the original motive of a particular area. It became the goal in conducting this study. Traditional motifs (Coastal Batik and Inland Batik) were data to be predicted using the method of Content-Based Image Retrieval (CBIR). With the implementation of feature extraction of Gray Level Co-Occurrence Matrices (GLCM) with a classification method using CBIR to calculate Canberra Distance, the level of accuracy of the classification results was obtained.