Egriva, Kristofer Pinem (2023) Analisis Sentimen Pengguna Twitter Terhadap Sea Games Vietnam 2021 Menggunakan Metode Naive Bayes. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.
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Abstract
Sport is an activity that is in great demand by many people around the world. All kinds of sports have a lot of enthusiasts, for example, football, badminton, basketball, volleyball, running and other sports. Southeast Asia is no exception, sports activities have many fans and have their own sporting events specifically participated in by Southeast Asian countries which we know as the Southeast Asian Games (Sea Games). It is held every two years and is attended by 11 ASEAN member countries. In 2021 the Sea Games was postponed for a year due to the Covid-19 pandemic. Because of this, there are many opinions that are scattered in the community about this sporting activity, both positive and negative responses, there are those who support the implementation of this activity and there are also those who reject this activity being held temporarily because the world is still in a pandemic situation. become a forum for the public to express their opinion on anything that happens in this world. As a forum for public opinion, various data from user tweets about the Sea Games 2021 Vietnam have been collected. This data can be processed and analyzed to understand the sentiments of Twitter users towards the event. Sentiment analysis is the process of extracting, processing data and understanding textual data automatically. Naïve Bayes is a machine learning algorithm that is often implemented in sentiment analysis. The results of this study are public sentiment towards the 2021 Sea Games on the Twitter social media page having positive opinions or sentiments with a percentage of 41.42%, sentiments that are neutral at 51.7%, and those with negative sentiments and 6.89%. Keywords: Sea Games 2021, sentiment, Naïve Bayes
Item Type: | Thesis (Undergraduate Thesis) |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Informatics > Information System |
Depositing User: | repository staff |
Date Deposited: | 05 Jul 2024 08:07 |
Last Modified: | 05 Jul 2024 08:07 |
URI: | http://repository.ittelkom-pwt.ac.id/id/eprint/10650 |
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