Identifikasi Topeng Bali Dengan Metode KNN (K Nearest Neighbor)
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Authors:
Ni Made Elvina Aryadhika Putri, I Gusti Agung Gede Arya Kadyanan, I Wayan Supriana, Cokorda Rai Adi Pramartha, Anak Agung Istri Ngurah Eka Karyawati, Ida Bagus Gede Dwidasmara
Abstract:
“Mask art is art with the form of a face covering that has various forms such as humans and animals and is an important element in dance and mask drama. Unfortunately, many tourists and also the public cannot know the name of the Balinese mask they see. To overcome this problem, a system was built to help people who want to know information about Balinese masks but do not know the names or types of Balinese masks. In developing a system that able to identify Balinese masks, KNN classification method is implemented as a method that helps identify Balinese masks. The image entered by the user is processed until a classification result is obtained which is then sent back to the system so that it can be displayed to the user. The results of the system evaluation show the percentage accuracy of the KNN algorithm is 85% with value of k = 3.”
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https://jurnal.harianregional.com/jlk/full-89086
Published
2022-07-16
How To Cite
PUTRI, Ni Made Elvina Aryadhika et al. Identifikasi Topeng Bali Dengan Metode KNN (K Nearest Neighbor).JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 11, n. 2, p. 405-410, july 2022. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/89086. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/JLK.2022.v11.i02.p19.
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Issue
Vol 11 No 2 (2022): JELIKU Volume 11 No 2, November 2022
Section
Articles
Copyright
This work is licensed under a Creative Commons Attribution 4.0 International License
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