Texture Analysis on Image Motif of Endek Bali using K-Nearest Neighbor Classification Method

Endek fabric Bali is one form of craft woven fabric of Balinese society. Endek fabric has a variety of motifs or designs, a lot of people does not know that Endek have the type based on the design motif. In this research will be carried out an analysis texture on the Image Motif of Endek Bali and then classify them into several classes based on the type pattern motif of Endek Bali. The first step in this research is to collect some Image of Endek with different motif, then transform image into a gray level image using Edge Detection and do the extraction using GLCM, after that performed data classification using KNN. Based on the analysis of all the grades K that have been tested, the value K with the most excellent level accuracy is on K = 15 and on Correlation component, with an accuracy percentage of 43.33%. Overall, the Cemplong motif is a motif that has recognition accuracy levels better than most other motifs, that with a percentage of 57.50%. There are quite a lot of motifs that are less precise Endek recognized at the time of classification. It’s because among the Endek motifs may have the similar texture. The purpose of this study is to analyze texture and classify image motif of Endek Bali so that later can be developed into an application or program that can help to recognize the type of fabric Endek Bali. And even better if the program is implemented on the mobile phone, it can facilitate the process of image acquisition and subsequent directly extracted and classified from the mobile phone and can produce accurate classification results. Keywords—Analysis; Texture; Image; Endek Bali; Edge Detection; GLCM; K-NN