Implementasi Algoritma K-Nearest Neighbor pada Perangkat Lunak Pengelompokan Musik untuk Menentukan Suasana Hati

Music is closely related to human psychology, this fact indicates that music can be associated with specific emotions and mood in humans. Any music that has been created has its own mood that radiates, and therefore has a lot of research in the field of Music Information Retrieval (MIR) has been developed to explore the mood of the music. This research resulted in a classification system of music on mood by using K-Nearest Neighbor algorithm. The system uses the data input in the form of music file formats mono * .wav in the refrain lasts 30 seconds, which in turn make the process of classification of music by using K-NN algorithm. The system generates output in the form of labels mood, contentment, Exuberance, depression and anxious. In general the results of the accuracy of the system by using KNN is good enough ie 86.55% on the value of k = 3, and the processing time classification of the average 0.01021 seconds perfile of music.