Skripsi

ANALISIS SENTIMEN TRENDING TOPIK DI MEDIA SOSIAL TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER

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Penilaian

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Twitter is a social media platform that contains information such as current news, personal biographies, and tweets from its users. Twitter has a feature called trending topics, which functions to identify specific popular topics. However, it is often difficult to understand the sentiment associated with these trending topics. Therefore, it is important to classify the sentiment of trending topics with the aim of understanding how people respond to and perceive popular topics on Twitter. The method used for sentiment analysis in this study is the naive Bayes classifier, and data validation is performed using k-fold cross-validation with fold values of 2,3,4,5,6,7,8,9 anda 10 to obtain the best accuracy model. The testing conducted using the RapidMiner application revealed that the best accuracy was achieved with the model at fold = 7, with an accuracy value of 65.55%, precision value of 59.71%, and recall value of 36.53%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307005159	T121986	T1219862023	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1219862023

Publisher

Indralaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Sriwijaya., 2023

Collation

xv, 66 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.754 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)

Prodi Sistem Informasi
Situs Jejaring Sosial, Sosial Media

Specific Detail Info

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Statement of Responsibility

ANUG

Other version/related

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