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All Journal Algoritme Jurnal Mahasiswa Teknik Informatika
Cahyati, Imelia Dwinora
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Computer Science & IT

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Journal : Algoritme Jurnal Mahasiswa Teknik Informatika

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Pengenalan Motif Songket Palembang Menggunakan Convolutional Neural Network dengan Arsitektur ResNet-50 Cahyati, Imelia Dwinora; Devella, Siska; Yohannes, Yohannes
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 5 No 1 (2024): Oktober 2024 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i1.9404

Abstract

Songket fabric is a cultural heritage of Indonesia woven with gold or silver threads, creating textiles that are not only visually captivating but also rich in cultural significance. Each motif on Palembang Songket reflects the traditions and beliefs of the community, where the selection of motifs is often tailored to specific event contexts. However, the recognition of several motifs with similar patterns presents unique challenges in the identification process. This study aims to implement a Convolutional Neural Network (CNN) method for classifying Palembang Songket motifs. The dataset used consists of images of Songket motifs, including Bintang Berantai, Naga Besaung, Nampan Perak, and Pulir. The ResNet-50 architecture is utilized as the classification model. The results indicate that the implemented model achieves an accuracy of 96% in recognizing these motifs, thereby contributing to the preservation and enhancement of understanding regarding the cultural richness of Palembang Songket.
Co-Authors Devella, Siska Wiwik Handayani