Jurnal Ilmiah Teknik Elektro
Jetri, Volume 21, Nomor 1, Agustus 2023

KLASIFIKASI GENRE MUSIK DENGAN MENGGUNAKAN METODE MACHINE LEARNING

Catherine Olivia Sereati (Atma Jaya Catholic University of Indonesia)
Hilarius Radix W. C (Unknown)
Lanny W Pandjaitan (Unknown)
Maria Angela Kartwidjaja (Unknown)

Article Info

Publish Date
31 Aug 2023

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

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Journal Info
Jurnal Ilmiah Teknik Elektro
Website

Abbrev

jetri

Publisher

Universitas Trisakti

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

Description

Jetri is a scientific journal aims to publish high quality and up to date articles in electrical engineering field. Its scope includes (but not limited to): - Power Systems: nonrenewable and renewable energy power generation, power transmission and distribution, power conversion, protection system, ...