Analisis Sentimen Publik pada Pembatalan Tuan Rumah Indonesia di Piala Dunia U-20 Menggunakan Metode FastText dan Algoritma Recurrent Neural Network (RNN)

NANDA, AAN EVIAN (2024) Analisis Sentimen Publik pada Pembatalan Tuan Rumah Indonesia di Piala Dunia U-20 Menggunakan Metode FastText dan Algoritma Recurrent Neural Network (RNN). Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

Indonesia's golden opportunity to participate in the world class soccer competition at the U-20 World Cup competition was wiped out, because FIFA gave a decision to revoke Indonesia's status as host of the U-20 World Cup. Netizens Indonesian netizens who felt disappointed expressed their opinions and became trending on social media Twitter. This research focuses on tweet sentiment analysis using combination of FastText embeddings method for word vectorization and using the LSTM type RNN algorithm for sentiment classification. The dataset used total of 9,645 data consisting of 4,141 positive data and 5,504 negative data taken in the time span of March 29, 2019. which were taken from March 29, 2023 to April 05, 2023. Results testing on the LSTM model provides the best performance with an accuracy value of 74.92%, precision 74.73%, recall 74.92%, and f1-score 74.77%. The conclusion of this research is that the majority of datasets have negative sentiment, which means that people are more likely to give negative opinions than to support Indonesian soccer. negative opinions rather than providing support to Indonesian soccer which is experiencing problems. experiencing problems. It is hoped that with this conclusion in the future people are more in control of their opinions and give positive opinions when Indonesia is experiencing problems. Keywords: Twitter, U-20 World Cup, Sentiment Analysis, FastText, RNN, LSTM.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Sihananto, Andreas Nugroho	NIDN0012049005	UNSPECIFIED
Thesis advisor	Rizki, Agung Mustika	NIDN0025079302	UNSPECIFIED

Subjects:

T Technology > T Technology (General)

Divisions:

Faculty of Computer Science > Departemen of Informatics

Depositing User:

Aan Evian Nanda

Date Deposited:

26 Apr 2024 07:11

Last Modified:

26 Apr 2024 07:11

URI:

https://repository.upnjatim.ac.id/id/eprint/21919

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