Authors:

I Nyoman Yusha Tresnatama Giri, Luh Arida Ayu Rahning Putri, Gst Ayu Vida Mastrika Giri, I Gusti Ngurah Anom Cahyadi Putra, I Made Widiartha, I Wayan Supriana

Abstract:

“The genre of music is a grouping of music according to their resemblance to one another and commonly used to organize digital music. To classify music into certain genres, one can do it by listening to the music one by one manually, which will take a long time so that automatic genre assignment is needed which can be done by a number of methods, one of which is the Modified K-Nearest Neighbor. Modified K-Nearest Neighbor method is a further development of its former method called KNearest Neighbor method which adds several additional processes such as validity calculations and weight calculations to provide more information in the selection class for the testing data. Research to find the best H value shows that the H = 70% of the training data is able to produce an accuracy of 54.100% with K = 5 and the proportion ratio of test data and training data is 20:80 (fold 5). The best H value is then used for further testing, which is to compare the K-Nearest Neighbor method with the Modified K-Nearest Neighbor method using two different proportions of test data and training data and each proportion of data also tests a different K value. The results of the classification comparison of the two methods show that the Modified K-Nearest Neighbor method, with the highest accuracy of 55.300% is superior to the K-Nearest Neighbor method with the highest accuracy of 53.300%. The two highest accuracies produced in each method were obtained using K = 5 and the proportion ratio of test data and training data is 10:90 (fold 10).”

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PDF:

https://jurnal.harianregional.com/jlk/full-82783

Published

2022-02-28

How To Cite

GIRI, I Nyoman Yusha Tresnatama et al. Music Genre Classification Using Modified K-Nearest Neighbor (MK-NN).JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 10, n. 3, p. 261-270, feb. 2022. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/82783. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/JLK.2022.v10.i03.p02.

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Issue

Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 2022

Section

Articles

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