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All Journal Journal of Sustainable Software Engineering and Information Systems
Husna Sarirah Husin
Taylor University

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Improving the Classification Accuracy of Parang Batik Motifs with High Visual Similarity Through the Integration of GLCM and MobileNetV2 Haryanto; Husna Sarirah Husin
Journal of Sustainable Software Engineering and Information Systems Vol. 2 No. 1 (2026): Journal of Sustainable Software Engineering and Information Systems
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jsseis.v2i1.158

Abstract

Background: Despite its high aesthetic value, automatic classification of Parang Surakarta batik is difficult due to the extreme textural similarities between sub-motifs. Standard CNN architectures, including MobileNetV2often fail to detect the subtle textural details that distinguish each variation of the motif. Aims: This study develops a hybrid classification model that combines manual and automated spatial texture features to improve identification accuracy on motifs with high visual similarity. Methods: Using a dataset that has been expanded to 120 original images (40 per class) which is then augmented to a total of 1,200 images to ensure stronger model generalization. This methodology hybrid GLCM-MobileNetV2architecture through transfer learning techniques. Features from both methods are combined through feature fusion before being classified using a Dense layer. Result: The hybrid GLCM-MobileNetV2model achieved an accuracy of 99%. This performance outperformed the pure MobileNetV2 method (66.67%) and GLCM-SVM (85%), demonstrating that texture features provide significant discriminatory power against similar repetitive patterns. Conclusion: The integration of GLCM and MobileNetV2 is highly effective for classifying visually similar batik motifs, achieving a superior accuracy of 99% compared to the pure MobileNetV2 (66.67%). This hybrid approach provides a robust and efficient solution for digital cultural preservation on mobile devices.
Co-Authors Haryanto, Haryanto