The Effect of Feature Selection on Music Genre Classification - Giri, I Nyoman Yusha Tresnatama; Putri, Luh Arida Ayu Rahning (JELIKU (Jurnal Elektronik Ilmu Komputer Udayana); Vol 9 No 4 (2021): JELIKU Volume 9 No 4, Mei 2021DO - 10.24843/JLK.2021.v09.i04.p13, 2021)
One of the things that affects classification results is the correlation of features to the class of a data. This research was conducted to determine the effect of the reduction of features (independent variable) that have the weakest correlation or have a distant relationship with the class (dependent variable). Bivariate Pearson Correlation is used as a feature selection method and K-Nearest Neighbor is used as a classification method. Results of the test showing that, 75.1% average accuracy was obtained for classification without feature selection, while using feature selection, average accuracy was obtained in the range of 75% - 79.3%. The average accuracy obtained by the selection of features tends to be higher compared to the accuracy obtained without selection of features.