EKSTRAKSI CIRI LOCAL BINARY PATTERN (LBP) DAN GRAY LEVEL CO-OCCURRENCE MATRIX (GLCM) PADA KASUS MOTIF BATIK YOGYAKARTA DENGAN PENGKLASIFIKASI SUPPORT VECTOR MACHINE (SVM)

• Main Author: Ndaru Aji Laksono, (Author)
• Format: Book
• Published: 2020-07-09.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Link Metadata

Summary

Batik is a craft that uses wax to draw certain patterns on wide fabric media. Yogyakarta Batik is one of the many varieties of batik in Indonesia. Ceplok motifs and kawung motifs are motifs owned by Yogyakarta batik. Both of motifs are the geometric motif. The motives are close to each other. Texture feature extraction using the local binary pattern (LBP) method and gray level co-occurrence matrix (GLCM) was used to make the Yogyakarta batik motif recognition system. LBP is a statistical characteristic in the first order while GLCM is a statistical characteristic in the second order. Support Vector Machine (SVM) is used as a method to classify Yogyakarta batik motifs by two classes, with name the ceplok and kawung classes. To find out the best feature extraction for the case of introducing Yogyakarta batik motifs, an accuracy calculation is performed. The results of this research are 55% accuracy on LBP, 75% accuracy on GLCM and 70% accuracy combined LBP and GLCM.

Item Description

http://repository.upnvj.ac.id/7127/1/ABSTRAK.pdf
http://repository.upnvj.ac.id/7127/2/AWAL.pdf
http://repository.upnvj.ac.id/7127/3/BAB%201.pdf
http://repository.upnvj.ac.id/7127/4/BAB%202.pdf
http://repository.upnvj.ac.id/7127/5/BAB%203.pdf
http://repository.upnvj.ac.id/7127/6/BAB%204.pdf
http://repository.upnvj.ac.id/7127/7/BAB%205.pdf
http://repository.upnvj.ac.id/7127/8/DAFTAR%20PUSTAKA.pdf
http://repository.upnvj.ac.id/7127/9/RIWAYAT%20HIDUP.pdf
http://repository.upnvj.ac.id/7127/10/LAMPIRAN.pdf
http://repository.upnvj.ac.id/7127/11/ARTIKEL.pdf