Combination of First Order Statistical Feature and Gray Level co-occurence Matrix for Cirebon Mask Classification

Indonesia culture captivates people both domes-tically and internationally. One of the prominent cultures is Cirebon Mask. There are five types of Cirebon masks: Panji, Samba, Rumyang, Tumenggung, and Kelana. Sadly, the Cirebon mask is already on the verge of extinction because of the local people do not want to learn and preserve the understanding of Cirebon mask. To prevent extinction, we digitise the mask and build a machine learning model to categorized the Cirebon Mask based on its type, which will be used as content-based image retrieval. In this work, we present texture features using a combination of first-order statistical features and GLCM features while K-Nearest Neighbour and Support Vector Machine acted as the classifier. The best accuracy of this research is 92.96 %