2020
DOI: 10.12962/j23373520.v9i1.51311
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Identifikasi Genre Musik dengan Menggunakan Metode Random Forest

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Cited by 8 publications
(10 citation statements)
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“…Using a voting system (highest count) to combine independent classifiers (CARTs) from the same distribution random forest produces classification forecasts. Reduced correlation can lower the outcome of random forest prediction errors, a characteristic of random forest (As Sarofi, Irhamah, & Mukarromah, 2020). Random Forest Formula (Leonardo, Pratama, & Chrisnatalis, 2020):…”
Section: A Machine Learningmentioning
confidence: 99%
“…Using a voting system (highest count) to combine independent classifiers (CARTs) from the same distribution random forest produces classification forecasts. Reduced correlation can lower the outcome of random forest prediction errors, a characteristic of random forest (As Sarofi, Irhamah, & Mukarromah, 2020). Random Forest Formula (Leonardo, Pratama, & Chrisnatalis, 2020):…”
Section: A Machine Learningmentioning
confidence: 99%
“…Musik dapat diorganisir berdasarkan artis, album, atau genre/subgenre. Genre/Subgenre merupakan cara organisasi musik yang paling umum [3], hal ini disebabkan mudahnya pendengar mencari musik dengan gaya yang sama atau sejenis untuk didengarkan sesuai deng an pref erensi masing-masing.…”
Section: Pendahuluanunclassified
“…Music can be divided based on music genres. Sarofi et al, (2020) argued that music is divided into several genres. In the Indonesian Dictionary (KBBI), stated that genre is defined as a grouping of music based on the similarities on the type of music or musical literature and on the basis of its form.…”
Section: Introductionmentioning
confidence: 99%