Skripsi

DETEKSI HATE SPEECH DAN ABUSIVE LANGUAGE DALAM KOMENTAR SOSIAL MEDIA X MENGGUNAKAN SUPPORT VECTOR MACHINE

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Penilaian

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Social media has become an important platform for users to interact, share opinions, and share information. However, it increases the risk of spreading harmful content such as hate speech and abusive language, which harms individuals and the online environment. This research aims to classify hate speech and abusive language using the Support Vector Machine method. The data used in this research is a collection of comments on social media X, through several stages, namely preprocessing, TF-IDF weighting, SVM model training, and model performance evaluation. The data set was tested with various values of parameter C, and the accuracy obtained after being tested with multiple values of parameter C, the model results from 68,0% at C = 0.1 to 75,6% at C = 10. Each metric, including accuracy, precision, recall, and F1 score, reached the optimal value at parameter C = 10, which indicates that a larger value of C can help improve the overall performance of the model.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407006954	T162754	T1627542024	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1627542024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xvi, 84 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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