@thesis{thesis,
		author={Agtriadi  Herman Bedi and FEBRIYANTI  AUDREY and Susanti  Meilia Nur Indah},
		title ={ANALISA SENTIMEN MASYARAKAT MENGGUNAKAN METODE NAIVE BAYES DALAM MELIHAT BUDAYA K-POP DI MEDIA SOSIAL (TWITTER)},
		year={2022},
		url={http://156.67.221.169/4880/},
		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.}
		}