Implementasi Metode K-Nearest Neighbor Dalam Mengklasifikasikan Jenis Suara Berdasarkan Jangkauan Vokal
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Authors:
Ni Made Putri Wahyuni, Luh Arida Ayu Rahning Putri, I Gusti Ngurah Anom Cahyadi Putra, Dewa Made Bayu Atmaja Darmawan, Made Agung Raharja, Agus Muliantara
Abstract:
“Humans have voice characteristics with different vocal ranges, namely the male voice consists of Tenor, Baritone, and Bass, while the female voice consists of Soprano, Mezzosoprano, and Alto. Determining the voice range, especially for a singer, requires a vocal trainer or musical instrument that is quite difficult to access. Therefore, a sound classification system created based on vocal range using the Harmonic Product Spectrum (HPS) feature extraction method and the K-Nearest Neighbors (KNN) classification method uses k parameters from 1 to 40. The test gets the highest accuracy on parameter k=8, which is 88.88%, so that from the resulting accuracy to prove the K-Nearest Neighbor (KNN) method gives good results in classifying the type of voice. Keywords: Classification, Vocal range, Harmonic Product Spectrum, K-Nearest Neighbors”
Keywords
Classification, Vocal range, Harmonic Product Spectrum, K-Nearest Neighbors
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PDF:
https://jurnal.harianregional.com/jlk/full-89310
Published
2022-07-20
How To Cite
WAHYUNI, Ni Made Putri et al. Implementasi Metode K-Nearest Neighbor Dalam Mengklasifikasikan Jenis Suara Berdasarkan Jangkauan Vokal.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 11, n. 1, p. 187-194, july 2022. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/89310. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/JLK.2022.v11.i01.p20.
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Issue
Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
Section
Articles
Copyright
This work is licensed under a Creative Commons Attribution 4.0 International License
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