Aplikasi Pengenalan Pola Batik Dengan Menggunakan Metode Gray-Level Cooccurrence Matrix

Ronald Kurniawan Tjondrowiguno, Rolly Intan, Kartika Gunadi


Indonesia is country with rich culture. Since October 2nd 2009 batik has been officially recognized by UNESCO as Indonesia’s authentic cultural heritage. In addition to its unique patterns, batik has a deep philosophical significance. However there is no application that can introduce many kinds of batik to the society. This application is expected to address that issue.

This application uses gray-level cooccurrence matrix to extract texture features from an image of batik. The texture features extracted from a number of batik images create a dataset which can be used to create a decision tree. The decision made by the decision tree is the isen presented in batik image.

Test results of batik tulis recognition is maximum accuracy of 47.62%, which is considered low. The reason for that is supposedly the lack of texture patterns in batik tulis.


Image Processing; GLCM; Artificial Intelligence; Machine Learning; Fuzzy Set; ID3; Decision Tree

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