Pratama, Aditya Putra (2022) KLASIFIKASI GENRE MUSIK INTERNASIONAL MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Music is a genre of music that is classified by the similarity of rhythmic, frequency and harmony depending on the content of the music. Genres are very important for people who really like music, especially for young people in today's millennial era because they group music genres based on what they like. This study uses a convolutional neural network algorithm to classify music genres while for feature extraction it uses Chroma stft, Spectral centroid, Spectral bandwidth, Spectral Rolloff, Root Mean Square Energy (RMSE), Zero_Crossing Rate, Mel-Frequency Cepstral Coefficients, Harmony, Tempo. , Perceptron. The results of this study, the first test resulted in a prediction accuracy of 58%, and for the second test it produced a prediction accuracy of 81%, for the third test it got an accuracy of 87% and for the accuracy results in the fourth test it yielded 91% and the fifth test resulted in a prediction accuracy of 90% and the sixth test got a prediction accuracy of 90%. Each test uses a different dataset of feature extraction results and a Convolutional neural network model to see which results are the best
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76.6 Computer Programming Q Science > QA Mathematics > QA76.87 Neural computers |
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| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | aditya putra pratama | ||||||||||||
| Date Deposited: | 26 Jul 2022 08:30 | ||||||||||||
| Last Modified: | 26 Jul 2022 08:30 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/8383 |
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