Analisis Sentimen Covid-19 Pada Media Sosial Dengan Model Neural Machine Translation

  • Zen Munawar Politeknik LP3I
  • Iswanto Universitas Nurtanio
  • Dandun Widhiantoro Politeknik Negeri Jakarta
  • Novianti Indah Putri Universitas Kebangsaan Republik Indonesia


Sentiment analysis, also known as opinion mining. Social media offers users to share their conditions and opinions in their daily lives. Much of the vast amount of textual content is currently available and techniques are needed to make meaningful use of the information by separating and examining it. Sentimental analysis can explore the opinions of social media users from the point of view. During the Covid-19 pandemic, the whole world is giving comments on social media. This study aims to understand the awareness and public perception of the Indonesian people about issues related to Covid-19 on social media. Data mining was carried out on comments from users of social media accounts kawalcovid19, opponentcovid19 id, and the ministry of health with a total of 54,250 comments divided into 32,494 in the first week and 21,756 in the second week. The research method of analyzing the data includes data processing and sentiment exploration analysis. Sentiment distribution results based on the first week were positive 75.68%, neutral 16.3%, negative 13.41% while the second week was positive 80.14%, neutral 9.03%, negative 4.84%. The results are the majority of comments in Indonesian and a mixed language. Sentiment analysis shows the positive reaction of the public to the front line and all the efforts of the health ministry in fighting the pandemic. This study concludes that sentiment analysis has proven to be very effective in producing useful knowledge in the discussion of Covid-19, especially on social media, gathering public perceptions and responses about the government's Covid-19 efforts, and providing a different point of view from the current situation on the ground.


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How to Cite
Munawar, Z., Iswanto, Widhiantoro, D., & Putri, N. I. (2022). Analisis Sentimen Covid-19 Pada Media Sosial Dengan Model Neural Machine Translation. Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal), 9(1), 15-20.