Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning
Songket is a woven fabric created by prying the threads and adding more weft to create an embossed decorative pattern on a cotton or silk thread woven background. While songket from many places share similar motifs, when examined closely, the motifs of songket from various regions differ, one of whi...
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| Format: | Article |
| Language: | English |
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Politeknik Negeri Padang
2022-12-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | https://joiv.org/index.php/joiv/article/view/1532 |
| _version_ | 1811159808653393920 |
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| author | Sudi Mariyanto Al Sasongko Erni Dwi Jayanti Suthami Ariessaputra |
| author_facet | Sudi Mariyanto Al Sasongko Erni Dwi Jayanti Suthami Ariessaputra |
| author_sort | Sudi Mariyanto Al Sasongko |
| collection | DOAJ |
| description | Songket is a woven fabric created by prying the threads and adding more weft to create an embossed decorative pattern on a cotton or silk thread woven background. While songket from many places share similar motifs, when examined closely, the motifs of songket from various regions differ, one of which is in the Province of West Nusa Tenggara, namely Lombok Island. To assist the public in recognizing the many varieties of Lombok songket motifs, the researchers used digital image processing technology, including pattern recognition, to distinguish the distinctive patterns of Lombok songket. The Gray Level Co-occurrence Matrix (GLCM) technique and Backpropagation Neural Networks are used to build a pattern identification system to analyze the Lombok songket theme. Before beginning the feature extraction process, the RGB color image has converted to grayscale (grayscale), which is resized. Simultaneously, a Backpropagation Neural Network is employed to classify Lombok songket theme variations. This study used songket motif photos consisting of a sample of 15 songket motifs with the same color theme that was captured eight times, four of which were used as training data and kept in the database. Four additional photos were utilized as test data or data from sources other than the database. When the system’s ability to recognize the pattern of Lombok songket motifs is tested, the maximum average recognition percentage at a 0° angle is 88.33 percent. In comparison, the lowest average recognition percentage at a 90° angle is 68.33 percent. |
| first_indexed | 2024-04-10T05:47:18Z |
| format | Article |
| id | doaj.art-4644ca515c404d75995da0615f44582b |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-04-10T05:47:18Z |
| publishDate | 2022-12-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-4644ca515c404d75995da0615f44582b2023-03-05T10:28:41ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042022-12-016483584110.30630/joiv.6.4.1532439Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation LearningSudi Mariyanto Al Sasongko0Erni Dwi Jayanti1Suthami Ariessaputra2University of Mataram, Mataram, 83125, IndonesiaUniversity of Mataram, Mataram, 83125, IndonesiaUniversity of Mataram, Mataram, 83125, IndonesiaSongket is a woven fabric created by prying the threads and adding more weft to create an embossed decorative pattern on a cotton or silk thread woven background. While songket from many places share similar motifs, when examined closely, the motifs of songket from various regions differ, one of which is in the Province of West Nusa Tenggara, namely Lombok Island. To assist the public in recognizing the many varieties of Lombok songket motifs, the researchers used digital image processing technology, including pattern recognition, to distinguish the distinctive patterns of Lombok songket. The Gray Level Co-occurrence Matrix (GLCM) technique and Backpropagation Neural Networks are used to build a pattern identification system to analyze the Lombok songket theme. Before beginning the feature extraction process, the RGB color image has converted to grayscale (grayscale), which is resized. Simultaneously, a Backpropagation Neural Network is employed to classify Lombok songket theme variations. This study used songket motif photos consisting of a sample of 15 songket motifs with the same color theme that was captured eight times, four of which were used as training data and kept in the database. Four additional photos were utilized as test data or data from sources other than the database. When the system’s ability to recognize the pattern of Lombok songket motifs is tested, the maximum average recognition percentage at a 0° angle is 88.33 percent. In comparison, the lowest average recognition percentage at a 90° angle is 68.33 percent.https://joiv.org/index.php/joiv/article/view/1532songketgray level co-occurrence matrix (glcm)neural networkbackpropagation. |
| spellingShingle | Sudi Mariyanto Al Sasongko Erni Dwi Jayanti Suthami Ariessaputra Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning JOIV: International Journal on Informatics Visualization songket gray level co-occurrence matrix (glcm) neural network backpropagation. |
| title | Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning |
| title_full | Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning |
| title_fullStr | Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning |
| title_full_unstemmed | Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning |
| title_short | Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning |
| title_sort | application of gray scale matrix technique for identification of lombok songket patterns based on backpropagation learning |
| topic | songket gray level co-occurrence matrix (glcm) neural network backpropagation. |
| url | https://joiv.org/index.php/joiv/article/view/1532 |
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