Analisis Sentimen Vaksinasi Booster Covid-19 pada Platform Twitter Menggunakan Metode Naïve Bayes

Main Author: Anggraeni, Dessy Tri; Universitas Gunadarma
Format: Article info Naïve Bayes application/pdf eJournal
Bahasa: eng
Terbitan: Universitas Bandar Lampung (UBL) , 2022
Subjects:
Online Access: http://jurnal.ubl.ac.id/index.php/expert/article/view/2812
http://jurnal.ubl.ac.id/index.php/expert/article/view/2812/2424
Daftar Isi:
  • Since the end of 2019, the Covid-19 virus hit the whole world, including in Indonesia. One of the efforts to deal with the Covid-19 virus is vaccination. In Indonesia, the government requires people to vaccinate 3 times, that are First Vaccination, Second Vaccination, and Booster Vaccination. The public's response to the booster vaccine are varies. This study aims to reveal public sentiment towards booster vaccine activities. The research was conducted by collecting tweet data from the Twitter platform. The research was conducted by collecting data tweets from Twitter. The method used is the Naïve Bayes Classifier because the method is simple, the process is fast, and it has a fairly high level of confidence. In this method, public sentiment is divided into three, that are positive, neutral, and negative. The results showed that most people responded positively to this booster vaccine activity with a value of 56.8%, neutral as much as 39.9%, and negative as much as 3.3% with an accuracy rate of 86%.