Efektifitas Algoritma K-NN dan Random Forest Dalam Mengenali Gender Berdasarkan Suara
on
Authors:
Berlin Pratama, I Ketut Gede Suhartana
Abstract:
“Human beings have the ability to recognize one’s gender through hearing and vision. In computer science this is called sound analysis, but often human sounds differ from the original after processing by computer. In this case, we try to differentiate human voices by gender using the K-Nearest Neighbor and Random Forest algorithms. The K-Nearest Neighbor algorithm has an accuracy of 76%, while Random Forest has an accuracy of 97%.”
Keywords
Keyword Not Available
Downloads:
Download data is not yet available.
References
References Not Available
PDF:
https://jurnal.harianregional.com/jnatia/full-92539
Published
2022-11-25
How To Cite
PRATAMA, Berlin; SUHARTANA, I Ketut Gede. Efektifitas Algoritma K-NN dan Random Forest Dalam Mengenali Gender Berdasarkan Suara.Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 1, n. 1, p. 279-284, nov. 2022. ISSN 3032-1948. Available at: https://jurnal.harianregional.com/jnatia/id-92539. Date accessed: 02 Jun. 2025.
Citation Format
ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian
Issue
Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Section
Articles
Copyright
This work is licensed under a Creative Commons Attribution 4.0 International License