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All Journal Jurnal Informasi Sains dan Teknologi (ISAINTEK)
Muhammad Nazaruddin
Universitas Gunadarma
Computer Science & IT Other

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Analisis Sentimen Masyarakat Pengguna Media Sosial Twitter Terhadap Motogp Mandalika Lombok Menggunakan Metode Bidirectional Encoder Representation From Transformers (BERT) Nelly Sofi; Tri Sulistyorini; Muhammad Nazaruddin
Jurnal Informasi, Sains dan Teknologi Vol. 6 No. 1 (2023): Juni: Jurnal Informasi Sains dan Teknologi
Publisher : Politeknik Negeri FakFak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/isaintek.v6i1.103

Abstract

The MotoGP One race in West Nusa Tenggara Lombok, Mandalika which was held on March 18 2022, received many responses or reactions from the public on social media, especially Twitter. There are those who agree and disagree about the holding of MotoGP in Mandalika, to find out the responses of the people who agree or disagree is needed that can process tweets data using the sentiment analysis method. The use of BERT (Bidirectional Encoder Representations from Transformers) for sentiment analysis produces a bidirectional language model that can understand the context of all words from a sentence. The dataset used goes through preprocessing stages such as case folding, data cleaning, tokenization, normalization, and removal of stopwords before sentiment analysis is carried out. This study uses several hyperparameters, namely a batch size of 32, the optimizer uses Adam with a learning rate of 3e-6 or 0.000003, and an epoch of 25. The evaluation results of the model obtain an accuracy of 55%. Precision for positive by 56%, neutral by 59%, and negative by 44%. Recall for positive is 74%, neutral is 29%, and negative is 54%. F1-score for positive is 64%, neutral is 38%, and negative is 48%.
Co-Authors Nelly Sofi Tri Sulistyorini