| |
| Dublin Core |
PKP Metadata Items |
Metadata for this Document |
| |
| 1. |
Title |
Title of document |
Identification of Papua Cenderawasih Batik Motifs using Local Binary Pattern and K-Nearest Neighbor |
| |
| 2. |
Creator |
Author's name, affiliation, country |
Dian Dwi Ariani; Universitas Handayani Makassar; Indonesia |
| |
| 2. |
Creator |
Author's name, affiliation, country |
Sitti Zuhriyah; Universitas Handayani Makassar; Indonesia |
| |
| 2. |
Creator |
Author's name, affiliation, country |
Eva Yulia Puspaningrum; Universitas Pembangunan Nasional "Veteran" Jawa Timur; Indonesia |
| |
| 2. |
Creator |
Author's name, affiliation, country |
Mahabintang Pallawabonang; Universitas Handayani Makassar; Indonesia |
| |
| 3. |
Subject |
Discipline(s) |
Teknik Informatika |
| |
| 3. |
Subject |
Keyword(s) |
Papuan batik motifs, Local Binary Pattern, K-Nearest Neighbor, image processing, classification. |
| |
| 4. |
Description |
Abstract |
Papua Island has natural and cultural richness wich is reflected in its batik motifs, such as the Cenderawasih and Tifa motifs. Although batik recognition technology has developed, systems capable of automatically identifying Papua batik motifs are still limited. This research aims to develop a texture recognition system using the Local Binary Pattern (LBP) feature extraction method and K-Nearest Neighbor (KNN) classification. The Cenderawasih motif dataset consists of 115 images, and the Tifa motif dataset consists of 120 images with an 80:20 composition for training and testing data. We tested the KNN model with various k values and found that k = 7 yielded the best results, with accuracy of 97.16%, precision of 97.10%, and F1-score of 97.10%. The developed GUI interface facilitates users in identifying batik motifs, providing prediction results, and texture visualization. The results of this study show that image processing technology could help protect Papuan batik. Future research could improve model accuracy by utilizing larger data sets and classification algorithms to make the models more accurate. |
| |
| 5. |
Publisher |
Organizing agency, location |
Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer |
| |
| 6. |
Contributor |
Sponsor(s) |
Merdeka Belajar – Kampus Merdeka (MBKM) UPN Veteran Jatim |
| |
| 7. |
Date |
(YYYY-MM-DD) |
2025-03-04
|
| |
| 8. |
Type |
Status & genre |
Peer-reviewed Article |
| |
| 8. |
Type |
Type |
|
| |
| 9. |
Format |
File format |
PDF |
| |
| 10. |
Identifier |
Uniform Resource Identifier |
https://sistemasi.org/index.php/stmsi/article/view/5008 |
| |
| 10. |
Identifier |
Digital Object Identifier (DOI) |
https://doi.org/10.32520/stmsi.v14i2.5008 |
| |
| 11. |
Source |
Title; vol., no. (year) |
Sistemasi: Jurnal Sistem Informasi; Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi |
| |
| 12. |
Language |
English=en |
en |
| |
| 13. |
Relation |
Supp. Files |
|
| |
| 14. |
Coverage |
Geo-spatial location, chronological period, research sample (gender, age, etc.) |
|
| |
| 15. |
Rights |
Copyright and permissions |
Copyright (c) 2025 Sistemasi: Jurnal Sistem Informasi
|