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

Pratama, Berlin
Suhartana, I Ketut Gede

Jurnal Nasional Teknologi Informasi dan Aplikasinya
Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022

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%.