ANALISA SENTIMEN MASYARAKAT MENGGUNAKAN METODE NAIVE BAYES DALAM MELIHAT BUDAYA K-POP DI MEDIA SOSIAL (TWITTER)
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
FEBRIYANTI, AUDREY
Agtriadi, Herman Bedi
Susanti, Meilia Nur Indah
Agtriadi, Herman Bedi
Susanti, Meilia Nur Indah
Subject
Teknik Informatika
Datestamp
2022-09-20 03:50:17
Abstract :
There is a lot of discussion about K-Pop culture among the public, one of which is on the Twitter social media platform. In the quotes on Twitter social media, many people have an opinion or judge about the existence of K-Pop culture. Various kinds of opinions and outpourings have been submitted so that they can be used by parties/institutions as a benchmark for the influence of K-Pop culture among the community. With this, the study aims to analyze public sentiment towards Kpop culture on Twitter social media so that it can be implemented into positive sentiments, negative sentiments, and neutral sentiments. With Sentiment Analysis and Naive Bayes techniques as classification, this research uses several processes with testing data from Twitter crawling as much as 590 data generated. From the testing data, the test produces an accuracy of 90%. In conclusion, the Naive Bayes method is shown to be able to capture sentiment information from social media.
There is a lot of discussion about K-Pop culture among the public, one of which is on the Twitter social media platform. In the quotes on Twitter social media, many people have an opinion or judge about the existence of K-Pop culture. Various kinds of opinions and outpourings have been submitted so that they can be used by parties/institutions as a benchmark for the influence of K-Pop culture among the community. With this, the study aims to analyze public sentiment towards Kpop culture on Twitter social media so that it can be implemented into positive sentiments, negative sentiments, and neutral sentiments. With Sentiment Analysis and Naive Bayes techniques as classification, this research uses several processes with testing data from Twitter crawling as much as 590 data generated. From the testing data, the test produces an accuracy of 90%. In conclusion, the Naive Bayes method is shown to be able to capture sentiment information from social media.
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