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All Journal Jurnal Ilmiah Teknik Elektro
Catherine Olivia Sereati
Atma Jaya Catholic University of Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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KLASIFIKASI GENRE MUSIK DENGAN MENGGUNAKAN METODE MACHINE LEARNING Catherine Olivia Sereati; Hilarius Radix W. C; Lanny W Pandjaitan; Maria Angela Kartwidjaja
Jetri : Jurnal Ilmiah Teknik Elektro Jetri, Volume 21, Nomor 1, Agustus 2023
Publisher : Website

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jetri.v21i1.15339

Abstract

This research discusses how to classify music genres using machine learning.. Music of the same genre usually shares specific characteristics related to instrumentation, rhythmic structure, and musical pitch. Music genres can be done using the Machine Learning method. The Machine Learning algorithms used in this study are K-Nearest Neighbor, Random Forest, and Naïve Bayes. Furthermore, this study will compare the accuracy of the three methods. The primary data used in this study is the result of downloading from the internet. Machine learning programming is used through the Google Colab platform with the Python programming language. From the analysis and testing results, it was found that the Random Forest method has the highest level of accuracy
Co-Authors Hilarius Radix W. C Lanny W Pandjaitan Maria Angela Kartwidjaja