Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm
Riau Batik, a treasured cultural heritage, faces challenges in its preservation due to limited public awareness of its unique motifs. This research aims to bridge the knowledge gap by developing a website-based classification system that can identify and recognize Riau batik patterns, offering round...
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| Format: | Article |
| Language: | English |
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Universitas Riau
2024-11-01
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| Series: | International Journal of Electrical, Energy and Power System Engineering |
| Subjects: | |
| Online Access: | https://ijeepse.id/journal/index.php/ijeepse/article/view/201 |
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| author | Dhea Amanda Ramadhan Dian Ramadhani |
| author_facet | Dhea Amanda Ramadhan Dian Ramadhani |
| author_sort | Dhea Amanda Ramadhan |
| collection | DOAJ |
| description | Riau Batik, a treasured cultural heritage, faces challenges in its preservation due to limited public awareness of its unique motifs. This research aims to bridge the knowledge gap by developing a website-based classification system that can identify and recognize Riau batik patterns, offering round-the-clock accessibility to users. By leveraging the Convolutional Neural Network (CNN) algorithm, the classification system was trained using a dataset of 1,440 images. The model was fine-tuned through optimization of batch size and epoch parameters to maximize classification accuracy. The training process culminated in a model with an accuracy of 89%, achieved using a batch size of 16 and 50 epochs. This system seeks to elevate public appreciation and knowledge of Riau Batik, thereby contributing to the preservation of its cultural and historical significance. The accessible classification tool presents a practical approach to ensuring the motifs and legacy of Riau Batik are preserved for future generations. The proposed CNN-based model demonstrates the potential to enhance digital engagement with traditional culture through modern technology, facilitating widespread recognition and appreciation of Riau's rich batik heritage. |
| format | Article |
| id | doaj-art-b03728fa9fde4ad3bc3df0f75c926448 |
| institution | Kabale University |
| issn | 2654-4644 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Universitas Riau |
| record_format | Article |
| series | International Journal of Electrical, Energy and Power System Engineering |
| spelling | doaj-art-b03728fa9fde4ad3bc3df0f75c9264482025-02-04T04:33:38ZengUniversitas RiauInternational Journal of Electrical, Energy and Power System Engineering2654-46442024-11-017320121110.31258/ijeepse.7.3.201-211201Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) AlgorithmDhea Amanda Ramadhan0Dian Ramadhani1Universitas Riau, IndonesiaUniversitas Riau, IndonesiaRiau Batik, a treasured cultural heritage, faces challenges in its preservation due to limited public awareness of its unique motifs. This research aims to bridge the knowledge gap by developing a website-based classification system that can identify and recognize Riau batik patterns, offering round-the-clock accessibility to users. By leveraging the Convolutional Neural Network (CNN) algorithm, the classification system was trained using a dataset of 1,440 images. The model was fine-tuned through optimization of batch size and epoch parameters to maximize classification accuracy. The training process culminated in a model with an accuracy of 89%, achieved using a batch size of 16 and 50 epochs. This system seeks to elevate public appreciation and knowledge of Riau Batik, thereby contributing to the preservation of its cultural and historical significance. The accessible classification tool presents a practical approach to ensuring the motifs and legacy of Riau Batik are preserved for future generations. The proposed CNN-based model demonstrates the potential to enhance digital engagement with traditional culture through modern technology, facilitating widespread recognition and appreciation of Riau's rich batik heritage.https://ijeepse.id/journal/index.php/ijeepse/article/view/201classification, cnn, deep learning, riau batik. |
| spellingShingle | Dhea Amanda Ramadhan Dian Ramadhani Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm International Journal of Electrical, Energy and Power System Engineering classification, cnn, deep learning, riau batik. |
| title | Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm |
| title_full | Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm |
| title_fullStr | Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm |
| title_full_unstemmed | Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm |
| title_short | Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm |
| title_sort | classification of riau batik motifs using the convolutional neural network cnn algorithm |
| topic | classification, cnn, deep learning, riau batik. |
| url | https://ijeepse.id/journal/index.php/ijeepse/article/view/201 |
| work_keys_str_mv | AT dheaamandaramadhan classificationofriaubatikmotifsusingtheconvolutionalneuralnetworkcnnalgorithm AT dianramadhani classificationofriaubatikmotifsusingtheconvolutionalneuralnetworkcnnalgorithm |