Reino Prajamukti, . (2021) KLASIFIKASI DAN ANALISIS SENTIMEN PADA DATA TWITTER MENGGUNAKAN ALGORTIMA NAÏVE BAYES (STUDI KASUS: TIMNAS SEPAKBOLA INDONESIA SENIOR, U-23, DAN U-19). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Social media not only serves as an effective communication medium, but can also be a place to accommodate public opinion. One of the social media that is widely used to accommodate these opinions is Twitter. Twitter users in Indonesia often express their opinions in all fields including sports, especially the Indonesian Football National Team. Various kinds of sentiments towards the Indonesian Football National Team can be seen on Twitter. Set against these conditions, research is needed on public opinion about the performance of the Indonesian Football National Team. One way is to conduct sentiment analysis of the Indonesian Football National Team on the social network Twitter using classification methods and Naïve Bayes algorithm to classify positive or negative tweets that people give about the Indonesian FootballNational Team. The results of sentiment analysis using algoritma Naïve Bayes on the classification of tweets about opinions against the Indonesian Football National Team went well with an accuracy value of 83%,then a positive precision value of 86%, a value of 86%.%, precision Negative of 81%, recall value of 78%,and specificity value of this study 87.5%using confusion matrix method based on data taken in January to May 2021. Keywords: Twitter, Sentiment Analysis, Indonesian Football National Team, Algortima Naïve Bayes
Item Type: | Thesis (Skripsi) |
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Additional Information: | [No. Panggil : 1710511079] [Pembimbing 1 : Jayanta] [Pembimbing 2 : Mayanda Mega Santoni] [Penguji 1 : Ermatita] [Penguji 2 : Nurul Chamidah] |
Uncontrolled Keywords: | Twitter, Sentiment Analysis, Indonesian Football National Team, Algortima Naïve Bayes |
Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) |
Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
Depositing User: | Reino Prajamukti |
Date Deposited: | 07 Jan 2022 08:35 |
Last Modified: | 07 Jan 2022 08:35 |
URI: | http://repository.upnvj.ac.id/id/eprint/14347 |
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