Analysis of Public Opinion on the Covid-19 Vaccine Through Social Media using the Nae Bayes Theory Algorithm


Aishiyah Saputri Laswi(1*); Munir Yusuf(2); Ulvah Ulvah(3); Bungawati Bungawati(4);

(1) Universitas Andi Djemma Palopo
(2) Institut Agama Islam Neger (IAIN) Palopo
(3) Universitas Cokroaminoto Palopo
(4) Institut Agama Islam Neger (IAIN) Palopo
(*) Corresponding Author

  

Abstract


This study aims to analyze the diverse public opinion on the Covid-19 Vaccine that appears through #(hastag) on Social Media pages, especially on social media Facebook and Twitter. The high number of deaths caused by COVID-19 is 144,227 people until 2022. The government requires the Indonesian people to be vaccinated starting from children aged 6 years is one of the government's efforts in the spread of the covid-19 virus. However, the use of complete vaccines in Indonesia has only reached 51.3% of the mandatory vaccine population, namely 140 of the 339 million people who should be fully vaccinated. If the target set by the government is not achieved, it is deemed necessary to conduct a sentiment analysis through social media on vaccines in Indonesia. Based on data that has been sampled from 1000 words that often appear from 320 both positive and negative, then analyzed and processed to find out how many positive and negative responses came in. Based on public opinion on the covid-19 vaccine that has been studied using the Nae Bayes algorithm, negative opinions that appear in the community quickly spread through Social Media pages, the data is then processed into several stages to test the level of truth through training data and test data. The results obtained using the Nae Bayes test are the Accuracy Value with a precession of 77.08% taken from the number of test data as many as 96 samples, then recall with a percentage of 97.87% based on positive data which is estimated to be correct with a positive opinion status with a total of 47 data samples. test with 1 positive data status which is still estimated to be negative. Furthermore, the percentage value of the specifics obtained is 65.30% of the 32 test data that are estimated to be true negative.


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