Open AccessKlasifikasi Genre Musik Menggunakan Metode Mel-Frequency Cepstrum Coefficients dan K-Nearest Neighbors Classifier
Author(s) -
Pandu Deski Prasetyo,
I Gede Pasek Suta Wijaya,
Ario Yudo Husodo
Publication year - 2019
Publication title -
jurnal teknologi informasi, komputer dan aplikasinya
Language(s) - English
Resource type - Journals
ISSN - 2657-0327
DOI - 10.29303/jtika.v1i2.41
Subject(s) - computer science , mel frequency cepstrum , classifier (uml) , jazz , speech recognition , point (geometry) , artificial intelligence , pattern recognition (psychology) , feature extraction , mathematics , art , visual arts , geometry
In the world of music, music has several types of genre genres that can be grouped, there are music genre pop, rock, blues, slow, jazz, metal, dangdut and many more. And for each person must have a genre favorite that is different from one another, but to distinguish it does not need to play music files one by one especially if the number of music files is a lot. Therefore, computer software is needed to distinguish each of these genres in order to make it easier for users to distinguish and group the types of music according to their wishes automatically. By using the MFCC and KNN methods as a classification solution to classify several types of genre streams can be easily resolved. The results achieved from this study reached 52,4% with a K = 13 as the nearest neighboring point.