Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)

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Classification of Pringgasela Typical Songket Using Multi Texton Co-occurrence Descriptor and K-Nearest Neighbor

Authors
Ridho Ilahi1, Fitri Bimantoro1, *, Ramaditia Dwiyansaputra1, Rani Farinda2
1Dept Informatics Engineering, Mataram University Jl, Majapahit 62, Mataram, Lombok NTB, Indonesia
2Computer Engineering, Vistula University, 3 Stokłosy, Warsaw, Poland
*Corresponding author. Email: bimo@unram.ac.id
Corresponding Author
Fitri Bimantoro
Available Online 26 December 2022.
DOI
10.2991/978-94-6463-084-8_30How to use a DOI?
Keywords
Image Classification; Pringgasela Songket; Texton; MTCD; KNN
Abstract

Songket is one of Indonesia's cultural heritages in traditional fabrics that are still preserved today. Pringgasela, a village located on Lombok Island has been producing Songket with distinct characteristics and various patterns. Generally, people are aware of the typical Pringgasela Songket pattern but the difference between one pattern and another is often unrecognized. Furthermore, information regarding the types of Pringgasela Songket has not been well documented. This study aims to build a model that can classify the Pringgalsela Songket patterns using Multi Texton Co-Occurrence Descriptor (MTCD) and K-Nearest Neighbor (KNN) methods. The data used in this study were 4700 images of Pringgasela's Songket, which were divided into training and test data. The highest accuracy obtained was 99.99, 100% precision, and 100% recall with k = 3, using manhattan distance calculation.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
Series
Advances in Computer Science Research
Publication Date
26 December 2022
ISBN
10.2991/978-94-6463-084-8_30
ISSN
2352-538X
DOI
10.2991/978-94-6463-084-8_30How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ridho Ilahi
AU  - Fitri Bimantoro
AU  - Ramaditia Dwiyansaputra
AU  - Rani Farinda
PY  - 2022
DA  - 2022/12/26
TI  - Classification of Pringgasela Typical Songket Using Multi Texton Co-occurrence Descriptor and K-Nearest Neighbor
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
PB  - Atlantis Press
SP  - 352
EP  - 366
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-084-8_30
DO  - 10.2991/978-94-6463-084-8_30
ID  - Ilahi2022
ER  -