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Classification of Traditional Balinese Kites Using CNN for Cultural Preservation Ni Wayan Sumartini Saraswati; Eddy Hartono; Ketut Jaya Atmaja; Welda Welda; I Dewa Made Krishna Muku
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 3 (2026): Article Research July 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i3.16181

Abstract

The digital preservation of cultural heritage has become increasingly important in sustaining local traditions amid rapid modernization. Balinese traditional kites represent a distinctive form of intangible cultural heritage with unique visual characteristics; however, their identification and classification are still largely based on subjective expertise. This research develops a Convolutional Neural Network (CNN)-based model for image classification to automatically recognize three primary types of Balinese traditional kites: Bebean, Janggan, and Pecukan. Beyond technical implementation, this research contributes to the development of a culturally specific visual dataset, addressing the limited representation of local heritage objects in mainstream computer vision research, which is predominantly based on global datasets of generic objects. A balanced dataset of 2,400 images was constructed and evaluated using 5-Fold Cross Validation to assess model stability and generalization capability. The proposed CNN model achieved an average validation accuracy of 91.5%, with balanced precision, recall, and F1-score across folds. Further evaluation on an independent test set of 282 images resulted in an accuracy of 87.94%, indicating a generalization gap of approximately 4%, which remains within an acceptable range. The results demonstrate that CNN-based classification can effectively support structured digital documentation of traditional kites. This study highlights the potential of computer vision not only as a technical tool, but also as a strategic approach to advancing data-driven cultural preservation and expanding AI applications within localized cultural contexts.
Co-Authors Alvin Limawan Susanto Andika, I Gede Atmaja, Ketut Jaya Baehaqi Christina Purnama Yanti Christina Purnama Yanti Christina Purnama Yanti Dewa Ayu Putu Rasmika Dewi Dewa Ayu Putu Rasmika Dewi Dewa Ayu Putu Rasmika Dewi Dewi Natalia, Sang Ayu Made Krisna Dewi, Dewa Ayu Putu Rasmika Dewi, Yesi Ratna Eddy Hartono Eddy Hartono Eddy Hartono Eddy Hartono Eddy Hartono Gusti Putu Sutrisna Wibawa I Dewa Made Krishna Muku I Dewa Made Krishna Muku I Dewa Made Krishna Muku I Gede Adi Sudi Anggara I Gusti Ayu Agung Diatri Indradewi I Kadek Agus Bisena I Kadek Agus Bisena I Kadek Putra Agung Darmawan I Ketut Setiawan I Made Andi Kertha Yasa I Made Sukarsa I Nyoman Tri Anindia Putra I Nyoman Yudha Chandra Dinata I Putu Agus Eka Darma Udayana I Putu Dedy Sandana I Putu Dedy Sandana I Putu Krisna Suarendra Putra I Wayan Agustya Saputra I Wayan Dharma Suryawan I Wayan Dharma Suryawan Ida Bagus Gede Sarasvananda Juniartini, Ni Komang Tri Kadek Budi Sandika Ketut Gede Darma Putra, I Ketut Jaya Atmaja Ketut Jaya Atmaja Ketut Laksmi Maswari Ketut Sepdyana Kartini Krismentari, Ni Kadek Bumi Krisna, Gede Gana Eka Made Sudarma MADE WAHYU ADHIPUTRA Maria Osmunda Eawea Monny Melinia Hutari Natalia, Sang Ayu Made Krisna Dewi Ni Komang Tri Juniartini Ni Luh Pangestu Widya Sari NI LUH PUTU AGETANIA . NI LUH PUTU MERY MARLINDA Ni Made Lisma Martarini Ni Wayan Mirah Senja Pertiwi Ni Wayan Wardani Nirwana, Ni Kade Ayu Pirozmand, Poria Poria Pirozmand Poria Pirozmand Poria Pirozmand Poria Pirozmand Pramana, I Gusti Kadek Candra Adi Cahya Pramest, Ni Luh Gede Sintia Pramita, Dewa Ayu Kadek Pramitha, Gede Dana Priscilla Desinta Achelya Putu Ananda Sitarasmi Putu Sugiartawan Putu Wirayudi Aditama Sandhiyasa, I Made Subrata Sari, Ni Luh Pangestu Widya Waas, Devi Valentino Wardani, Ni Wayan Weizhi Song Welda