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All Journal Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Fathul Am
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Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science

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Klasifikasi Batik Pekalongan Berdasarkan Citra dengan Metode GLCM dan JST Backpropagation Fathul Am; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.532

Abstract

Batik is an Indonesian cultural heritage that is internationally recognized by UNESCO. However, knowledge about the types of batik, especially traditional Pekalongan batik, is increasingly forgotten due to globalization. This research aims to create a Pekalongan traditional batik image classification system through Gray Level Co-Occurrence Matrix (GLCM) feature extraction and Artificial Neural Network (ANN) classification method. This system aims to make it easier for people to identify Pekalongan batik motifs without requiring special skills. The results showed that the GLCM and JST methods can be used to classify Pekalongan batik can predict correctly. The use of JST Backpropagation architecture with 3 hidden layers resulted in train data accuracy of 46.6% and test data accuracy of 55.5%. This system is expected to help preserve the cultural heritage of batik and increase public understanding of Pekalongan batik motifs.
Co-Authors Enny Itje Sela