Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika
Yullyana, Yullyana
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Sinkron : Jurnal dan Penelitian Teknik Informatika

 1 
Content-Based Image Retrieval for Songket Motifs using Graph Matching Yullyana, Yullyana; Irmayani, Deci; Hasibuan, Mila Nirmala Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11411

Abstract

Indonesia is a country that has abundant cultural wealth. One of the characteristics of Indonesian culture is Songket. Songket is a typical Malay woven cloth that has many variants of motifs, each of which represents a different meaning and philosophy. Songket is often found in Sumatra Island with different motifs in each region. With so many types of songket motifs, not everyone can recognize and distinguish between one songket motif and another, even Indonesian citizens themselves. With the help of computers, it is easier to find information about a songket motif or to find a similar songket motif. The field that can play a role in solving this problem is Content-Based Image Retrieval (CBIR). This study aims to carry out a content retrieval process on the songket core motif using graph matching-based processing. In this study, the method used is felzenzswalb segmentation, and graph matching through the VF2 isomorphism algorithm and graph edit distance. The number of songket core motif images used as data is 180 data in the form of color images measuring 64 x 64 pixels. Based on the results of the study, it was found that the optimal graph matching algorithm and parameters in this study were the VF2 algorithm for artificial images with an f-1 score of 91.05%, and Graph Edit Distance with GED≤8 parameters for songket motif images with an f1-score. by 53.36%.
Co-Authors Hasibuan, Mila Nirmala Sari Irmayani, Deci