Decoding and preserving Indonesia's iconic Keris via A CNN-based classification
The present study explores the domain of Keris classification by employing advanced Convolutional Neural Networks (CNNs) as a potent technique for identifying subtle patterns and cultural characteristics inherent in these renowned Indonesian daggers. The study has presented encouraging findings abou...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Telematics and Informatics Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772503024000069 |
| _version_ | 1797260302742454272 |
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| author | Aji Prasetya Wibawa Anik Nur Handayani Mochammad Rafli Muharom Rukantala Muhammad Ferdyan Lalu Agung Purnama Budi Agung Bella Putra Utama Felix Andika Dwiyanto |
| author_facet | Aji Prasetya Wibawa Anik Nur Handayani Mochammad Rafli Muharom Rukantala Muhammad Ferdyan Lalu Agung Purnama Budi Agung Bella Putra Utama Felix Andika Dwiyanto |
| author_sort | Aji Prasetya Wibawa |
| collection | DOAJ |
| description | The present study explores the domain of Keris classification by employing advanced Convolutional Neural Networks (CNNs) as a potent technique for identifying subtle patterns and cultural characteristics inherent in these renowned Indonesian daggers. The study has presented encouraging findings about the identification of Pamor, Dhapur, and Tangguh categories. However, it is crucial to recognise and confront the inherent constraints associated with this research. The key constraints of the study pertain to the diversity of data, accuracy of labeling, generalizability of the model, and ethical considerations. The acquisition of a comprehensive dataset that effectively encompasses the whole range of Keris patterns offers a significant obstacle. Furthermore, it is crucial to pay careful attention to the accuracy of labeling, since it can be influenced by the subjective character of Keris classification. The important worry lies in guaranteeing the model's capacity to generalise to Keris images that have not been previously encountered, as well as its ability to comprehend and explain its decision-making process. The careful establishment of ethical frameworks is necessary to address ethical problems related to cultural sensitivity and the potential misuse of AI outputs in the realm of cultural heritage. Nevertheless, these constraints offer significant perspectives on potential areas for future investigation and enhancement. Future endeavours may prioritise the augmentation and broadening of the dataset, fostering collaboration with specialists in cultural domains, improving the interpretability of the model, and effectively addressing ethical considerations. The present study not only exhibits potential for expanding artificial intelligence in the domain of cultural preservation, but also contributes to a more profound understanding and recognition of the complex artistry and historical significance encapsulated within the Keris. |
| first_indexed | 2024-03-08T12:46:44Z |
| format | Article |
| id | doaj.art-cb08e5e7490145e8946763e54590c5d5 |
| institution | Directory Open Access Journal |
| issn | 2772-5030 |
| language | English |
| last_indexed | 2024-04-24T23:23:10Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Telematics and Informatics Reports |
| spelling | doaj.art-cb08e5e7490145e8946763e54590c5d52024-03-16T05:09:59ZengElsevierTelematics and Informatics Reports2772-50302024-03-0113100120Decoding and preserving Indonesia's iconic Keris via A CNN-based classificationAji Prasetya Wibawa0Anik Nur Handayani1Mochammad Rafli Muharom Rukantala2Muhammad Ferdyan3Lalu Agung Purnama Budi4Agung Bella Putra Utama5Felix Andika Dwiyanto6Department of Electrical Engineering and Informatics, Faculty of Engineering, Universitas Negeri Malang, Jl. Semarang no. 5, Malang 65145, Indonesia; Corresponding author.Department of Electrical Engineering and Informatics, Faculty of Engineering, Universitas Negeri Malang, Jl. Semarang no. 5, Malang 65145, IndonesiaDepartment of Electrical Engineering and Informatics, Faculty of Engineering, Universitas Negeri Malang, Jl. Semarang no. 5, Malang 65145, IndonesiaDepartment of Electrical Engineering and Informatics, Faculty of Engineering, Universitas Negeri Malang, Jl. Semarang no. 5, Malang 65145, IndonesiaDepartment of Electrical Engineering and Informatics, Faculty of Engineering, Universitas Negeri Malang, Jl. Semarang no. 5, Malang 65145, IndonesiaDepartment of Electrical Engineering and Informatics, Faculty of Engineering, Universitas Negeri Malang, Jl. Semarang no. 5, Malang 65145, IndonesiaFaculty of Computer Science, AGH University of Kraków, al. Adama Mickiewicza 30, Kraków 30-059, PolandThe present study explores the domain of Keris classification by employing advanced Convolutional Neural Networks (CNNs) as a potent technique for identifying subtle patterns and cultural characteristics inherent in these renowned Indonesian daggers. The study has presented encouraging findings about the identification of Pamor, Dhapur, and Tangguh categories. However, it is crucial to recognise and confront the inherent constraints associated with this research. The key constraints of the study pertain to the diversity of data, accuracy of labeling, generalizability of the model, and ethical considerations. The acquisition of a comprehensive dataset that effectively encompasses the whole range of Keris patterns offers a significant obstacle. Furthermore, it is crucial to pay careful attention to the accuracy of labeling, since it can be influenced by the subjective character of Keris classification. The important worry lies in guaranteeing the model's capacity to generalise to Keris images that have not been previously encountered, as well as its ability to comprehend and explain its decision-making process. The careful establishment of ethical frameworks is necessary to address ethical problems related to cultural sensitivity and the potential misuse of AI outputs in the realm of cultural heritage. Nevertheless, these constraints offer significant perspectives on potential areas for future investigation and enhancement. Future endeavours may prioritise the augmentation and broadening of the dataset, fostering collaboration with specialists in cultural domains, improving the interpretability of the model, and effectively addressing ethical considerations. The present study not only exhibits potential for expanding artificial intelligence in the domain of cultural preservation, but also contributes to a more profound understanding and recognition of the complex artistry and historical significance encapsulated within the Keris.http://www.sciencedirect.com/science/article/pii/S2772503024000069KerisPamorDhapurTangguhCultural preservationCNN |
| spellingShingle | Aji Prasetya Wibawa Anik Nur Handayani Mochammad Rafli Muharom Rukantala Muhammad Ferdyan Lalu Agung Purnama Budi Agung Bella Putra Utama Felix Andika Dwiyanto Decoding and preserving Indonesia's iconic Keris via A CNN-based classification Telematics and Informatics Reports Keris Pamor Dhapur Tangguh Cultural preservation CNN |
| title | Decoding and preserving Indonesia's iconic Keris via A CNN-based classification |
| title_full | Decoding and preserving Indonesia's iconic Keris via A CNN-based classification |
| title_fullStr | Decoding and preserving Indonesia's iconic Keris via A CNN-based classification |
| title_full_unstemmed | Decoding and preserving Indonesia's iconic Keris via A CNN-based classification |
| title_short | Decoding and preserving Indonesia's iconic Keris via A CNN-based classification |
| title_sort | decoding and preserving indonesia s iconic keris via a cnn based classification |
| topic | Keris Pamor Dhapur Tangguh Cultural preservation CNN |
| url | http://www.sciencedirect.com/science/article/pii/S2772503024000069 |
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