Analisis Sentimen Komentar Netizen Twitter Terhadap Fanboy NCT Menggunakan Naïve Bayes Classifier. (Sentiment Analysis of Twitter Netizens' Comments on NCT Fanboy Using Naïve Bayes Classifier).

Ardisavira, Efrina Ashfadiniyya (2024) Analisis Sentimen Komentar Netizen Twitter Terhadap Fanboy NCT Menggunakan Naïve Bayes Classifier. (Sentiment Analysis of Twitter Netizens' Comments on NCT Fanboy Using Naïve Bayes Classifier). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

Twitter is one of the most widely accessed social media in Indonesia. Users can share messages and information discussing various topics or issues. This research uses a quantitative content approach and Naïve Bayes Classifier sentiment analysis method to find out how Twitter netizens comment on NCT fanboys. Twitter data was collected through crawling data techniques with the tweet keyword "fanboy nct" in Indonesian language between October 3, 2022 – April 3, 2023. The labeling of positive, negative, and neutral sentiments in the text is determined based on the concept of attitude change in the Social Judgment Theory proposed by Muzafer Sherif. From 2 (two) data scenarios involving 408 clean datasets, scenario 1 became the most optimal experiment that resulted in sentiment positive 70,3% (287 data), negative 6,1% (25 data), and neutral 23,5% (96 data). The evaluation of confusion matrix obtained precision class 95,07%, recall 98,72%, and accuration 98,28%. The high test percentage value indicates that the performance of Naïve Bayes is stable and excellent in classifying sentiment.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: sentiment analysis, NCT fanboys, Naïve Bayes Classifier, RapidMiner, Twitter
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Fakultas Ilmu Sosial dan Ilmu Politik > Program Studi Ilmu Komunikasi
Depositing User: Efrina Ashfadiniyya Ardisavira
Date Deposited: 06 Mar 2024 02:36
Last Modified: 12 Jun 2024 04:09
URI: http://repository.untag-sby.ac.id/id/eprint/31069

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