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Abstract
Batik Bomba is a traditional textile of Kaili ethnic located in Kota Palu of Sulawesi Tengah. Batik
Bomba is one of Indonesia's cultural richness which has unique patterns and motifs. The unique
patterns found in Batik Bomba have a philosophical meaning in the life of Kaili ethnic. Bomba
batik motif image has many varieties making it difficult to recognize every motive variety. To
recognize each motive image Batik Bomba we must be known special characteristics of each
motive. This research will classify traditional batik Bomba Kaili motif with the stage of acquisition,
preprocessing, texture feature extraction and classification stages. The texture features of Bomba
batik image are obtained from feature extraction process using Gray Level Co-occurrence matrices
(GLCM) with angles 0, 45, 90 and 135. The texture features of each Bomba batik motif will be
classified using Linear Support Vector Machine (LSVM) method. The results obtained in this study
is the value of classification accuracy based on the value of texture characteristics at an angle 0
of 74.2%, angle 45 of 64.5%, angle 90 of 66.7% and 135 of 67.5%. The merger of all features of
Batik Bomba motif image in all angles resulted in the accuracy of classification at the training
phase to 80.65% and in the testing phase yielded an accuracy of 77.14%.
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