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DETEKSI KATA KASAR DALAM LIRIK LAGU BERBAHASA INGGRIS MENGGUNAKAN MODEL BERT

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Penilaian

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Music plays a significant role through digital streaming platforms, while concerns about offensive language in lyrics, especially among young listeners, require attention. This study develops a BERT-based model to detect offensive language in English song lyrics. The dataset comprises 3,598 lyrics, divided into training 2,878 data, validation 360 data, and test 360 data. Experiments tested 12 parameter scenarios involving variations in learning rate 2e-5, 3e-6, 5e-5, batch size 16 and 32, and freeze layers 6 and 8. Evaluation used confusion matrix and metrics including accuracy, precision, recall, and F1-score. Results showed the model detected offensive language with 93.06% accuracy using learning rate 3e-6, batch size 16, and 8 freeze layers, demonstrating BERT's effectiveness for this task despite some classification errors due to sentence structure similarities.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507002775	T173236	T1732362025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1732362025

Publisher

: Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

vii, 99 hlm.: Ilus., tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

EM

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