Abstract

The development of information technology today has experienced very rapid growth. One of the developments in information technology, namely social media such as Twitter, Facebook, and Youtube, are some of the most popular communication media in today's society. Twitter is often used to express emotions about something, either praising or criticizing in the form of emotion. Human emotions can be categorized into five basic emotions, namely love, joy, sadness, anger, and fear. Twitter users' emotional tweets can be known as opinion or sentiment analysis (opinion analysis or sentiment analysis). Sentiment analysis is also carried out to see opinions or tendencies towards a problem or policy, whether they tend to have negative or positive opinions. The COVID-19 vaccine has become one of the discussions with a fairly high intensity on social media. Vaccine-related tweets have increased as government policies evolve. The responses of netizens also varied, ranging from clinical trials of vaccines, free vaccines, vaccine effectiveness, halal vaccines, to the implementation of vaccinations. This research produces a system that can analyze tweet sentiment related to the covid 19 vaccine in Indonesia where the tweet is obtained using the Twitter API. This system uses the Multinominal Naive Bayes method for the classification process.

Highlights

  • The development of information technology today has experienced very rapid growth

  • Human emotions can be categorized into five basic emotions

  • Twitter users' emotional tweets can be known as opinion or sentiment analysis

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Summary

Pendahuluan

Perkembangan teknologi informasi saat ini telah mengalami pertumbuhan yang sangat pesat [Yustiani and Yunanto, 2017], Salah satu perkembangan teknologi informasi yakni Media sosial seperti Twitter, Facebook, dan Youtube merupakan beberapa media perangkat komunikasi terpopuler di masyarakat saat ini. Emosi tweet para pengguna twitter dapat dikenali dengan analisis opini atau sentimen (opinion analysis atau sentiment analysis [Rizal, 2017]). Analisis sentimen juga dilakukan untuk melihat pendapat atau kecenderungan opini terhadap sebuah masalah maupun kebijakan, apakah cenderung beropini negatif atau positif terhadap suatu tokoh tertentu [Rizal, 2017]. Oleh karena itu dibutuhkan sebuah sistem yang dapat menganalisis sentimen, terutama tweet yang berbahasa Indonesia. Vaksin covid 19 menjadi salah satu pembahasan dengan intensi cukup tinggi di media sosial. Pro & kontra ini banyak di bicarakan oleh masyarakat Indonesia melalui media sosial Twitter. Penelitian ini menghasilkan sebuah sistem yang dapat menganalisis sentimen tweet yang berhubungan dengan vaksin covid 19 di Indonesia dimana tweet tersebut didapat menggunakan Twitter API. Analisis Pro Kontra Vaksin Covid 19 Menggunakan Sentiment Analysis Sumber Media Sosial Twitter

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