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k-Nearest Neighbor (k-NN) Classification for Recognition of the Batik Lampung Motifs by Andrian, R; Naufal, M A; Hermanto, B; Junaidi, A; Lumbanraja, F R is a Physics and Astronomy article available to read on EtoBox.

What is k-Nearest Neighbor (k-NN) Classification for Recognition of the Batik Lampung Motifs about?

## Abstract Batik is a famous name of a traditional fabric from Java. It has been admitted as one if the traditional cultural heritage of Indonesia by UNESCO since October 2^nd^, 2009. Over the time, Batik is copied and modified by many regions in Indonesia resulting some new unique motifs. Batik Lampung is an sample of them. This paper deals with the k-Nearest Neighbor classification of the motifs (pattern) of the Batik Lampung. The known motifs of Batik Lampung consist of __Jung Agung, Siger Kembang Cengkih, Siger Ratu Agung,__ and __Sembagi__. The original image samples are stored in RGB. They are firstly resized into 50 x 50 pixels and then converted to grayscale image. To recognize them, the Gray Level Co-Occurence Matrix (GLCM) feature is extracted and k-Nearest Neighbor (k-NN) with values of k = 3, 5, 7, 9, 11 and orientation angle of 0^0^ 45^0^, 90^0^, 135^0^ is applied to classify the motifs. The best accuracy is achieved at the rate 97,96% for k = 7 and angle135^0^.

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Author

Andrian, R; Naufal, M A; Hermanto, B; Junaidi, A; Lumbanraja, F R

Publisher

Institute of Physics; IOP Publishing (ISSN 1742-6588)

Published

2019

Language

EN

Field

Physics and Astronomy (Physical Sciences)