Efektifitas Algoritma K-NN dan Random Forest Dalam Mengenali Gender Berdasarkan Suara - Pratama, Berlin; Suhartana, I Ketut Gede (Jurnal Nasional Teknologi Informasi dan Aplikasnya; Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022DO - 10.24843/JNATIA.2022.v01.i01.p33, 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%.