COMMAX 2020 UiTM Kampus Kuala Terengganu

Malaysian Batik is a batik textile art of Malaysia especially on the East Coast of Malaysia (Kelantan and Terengganu ).The method of Malaysian batik making is also quite different from those of Indonesian Javanese batik, the pattern is larger and simpler, it is seldom or never uses canting to create intricate patterns and rely heavily on brush painting method to apply the color on fabrics. Thus, it makes it difficult in classifying any design and motifs from different states in East Coast. Many Malaysian people cannot recognize the pattern name of batik that they wear or see. Furthermore, the varieties of batik increase each year, so batik pattern becomes harder to be identified. In this study, the proposed of this system is to classification of Kelantan and Terengganu batik pattern using Backpropagation Artificial Neural Networks and Gray Level Co-Occurrence Matrix (GLCM) features which includes contrast, correlation, energy and homogeneity. The step of the classification process begins with changing the image of batik from the color image to the grayscale image. Next, the value are extracted from GLCM features and used as a parameter in the classification process. Based on the results of testing using 50 test images, the accuracy value was 87.94% and the precision value was 80.64%. Moreover, the result can be obtained when using this system prototype to classify of batik images.