@thesis{thesis,
		author={Aulia  Ashda Faricha and Sudirman  M. Yoga Distra and Yosrita  Efy},
		title ={Identifikasi Motif Batik Tulis Wonosobo dengan Metode Gray Level Co-Occurrence Matrix (GLCM)},
		year={2019},
		url={http://156.67.221.169/4359/},
		abstract={Various Batik becomes one of the characteristics of the Indonesian region is no exception of Wonosobo. Many types and similarities of batik make it difficult to recognize the type of batik for sure. This research aims to computerize the process of identification of the Wonosobo batik motif by applying the method of the Gray Level Co-occurrence Matrix (GLCM). This method is one of the statistical methods that can be used to analyze feature extraction. After the characteristic extraction of each batik motif is known, the next stage is classification. Batik motifs will be classified according to the test image into a predefined group or class, at the stage of this classification method used is the method K-Nearest Neighbour (K-NN). The test data is used in the form of a Wonosobo batik image of 256x256 pixels formatted as. jpg as much as 15 data. From each type of highest accuracy batik is found in Carica batik is 85.71% and the accuracy of horse braid batik is 66.67% and 83.3% against batik Purwaceng. Hence the overall accuracy of the system is 83.3%.}
		}