Abstract
Besurek Batik is a characteristic of Bengkulu province, Besurek motifs are Rafflesia, Calligraphy, Paku Niches, Moon, Kuau Bird, and Jasmine. Besurek batik has high complexity in its manufacture and has many different types of motifs, therefore the identification of Besurek cloth in Bengkulu Province makes it easier to classify batik motifs and can also be an effort to preserve the culture of Bengkulu province. A feature extraction and method are used to classify Besurek type images of Bengkulu province using feature extraction Gray Level Co-Occurrence Matrix (GLCM) where glcm is used for feature extraction analysis, then classified using the K-Nearest Neighbor Algorithm (KNN). Based on the results of the analysis obtained from the Besurek motif, namely with an accuracy value of 0.93333, a recall of 0.93333 and a precision value of 0.94444 with an average value of 0.938856 at an angle of 1350.
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