Efektifitas Algoritma K-NN dan Random Forest Dalam Mengenali Gender Berdasarkan Suara

  • Berlin Pratama Universitas Udayana
  • I Ketut Gede Suhartana Universitas Udayana

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%.

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 Aplikasinya (JNATIA), [S.l.], v. 1, n. 1, p. 279-284, nov. 2022. Available at: <https://ojs.unud.ac.id/index.php/jnatia/article/view/92539>. Date accessed: 27 jan. 2023.

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.