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All Journal KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Dewa Sukietra
Universitas Kalbis
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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Journal : KALBISIANA Jurnal Sains, Bisnis dan Teknologi

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Aplikasi Rekomendasi Musik Berdasarkan Klasifikasi Genre Menggunakan Convolutional Neural Networks Dewa Sukietra
KALBISIANA Jurnal Sains, Bisnis dan Teknologi Vol. 10 No. 1 (2024): Kalbisiana
Publisher : UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbisiana.v10i1.3527

Abstract

Convolutional Neural Network can be implemented on various deep learning approach for scientific or problem solving real world case. This research discusess implementing Convolutional Neural Network for music genre classification. Researcher will classified 8 genres music on this research. Music will be converted first to MFCC so its features can be extracted. Researcher use GTZAN Dataset as the base line for Convolutional Neural Network to learn each feature on a bunch of genres. Validation Accruacy with GTZAN dataset is 79% and Real world classification resulting in 60%. The classification progam can be used on android devices. This research also serve music suggestions based the result of predicted genre.
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