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All Journal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika
Ahmad Abdul Hadi
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science

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ENSEMBLE MAJORITY VOTING UNTUK ANALISIS SENTIMEN DAN EMOSI PADA KOMENTAR YOUTUBE: STUDI KASUS RESIDENT EVIL 4 REMAKE Ahmad Abdul Hadi; Priskila, Ressa; Viktor Handrianus Pranatawijaya; Kristianti, Novera
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i2.22397

Abstract

Currently, social media can be said to be one of the important things in the fields of marketing, broadcasting and entertainment, such as the gaming industry. In this case, Sentiment Analysis and Emotion Detection can be a tool for understanding the public's response and perception of the content presented. One of them is for the game Resident Evil 4 Remake, which was announced on March 24, 2023, and received a lot of public response on various social media platforms such as YouTube, one of which received responses in the form of 7177 comments between June 3 2022 and February 9, 2024. The research methodology used includes data collection methodology and simulation methodology, by combining the Naive Bayes algorithm, SVM and BERT using the Majority Voting method where these algorithms were previously trained using two different datasets which showed Naive Bayes performance with an accuracy of 84%, SVM with 89%, BERT with 93% and the Majority Voting Method with 90% accuracy with training using the Resident Evil 4 Remake dataset. And in training with the Steam Game Review dataset, Naive Bayes and SVM were obtained with an accuracy of 53%, BERT with 66%, and the Majority Voting Method with an accuracy of 57%. The Majority Voting classification model trained on the Resident Evil 4 dataset was used to perform Sentiment Analysis classification on comments from the YouTube video entitled "Resident Evil 4 Remake: Reveal Trailer" from the IGN Channel. The ratio of positive and negative sentiments was 60.2% and 39%. .8% with the frequency of emotions of anger, excitement and anticipation appearing most frequently.
Co-Authors Kristianti, Novera Priskila, Ressa Viktor Handrianus Pranatawijaya