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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA
Muhammad Hasyim Asyari
Universitas Amikom Purwokerto, Banyumas
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Klasifikasi Sentimen Publik Terhadap Jenis Vaksin Covid-19 yang Tersertifikasi WHO Berbasis NLP dan KNN Primandani Arsi; Iphang Prayoga; Muhammad Hasyim Asyari
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5418

Abstract

The corona virus epidemic became an epidemic at the end of 2019 in the world. Some people are going through a pandemic with fear or even just being normal. The expression of fear, they discussed on social media. Now, social media is a means for some people to express their emotions namelly twitter. In order to end this pandemic the company is trying to develop a covid-19 vaccine, such as Pfizer, AstraZeneca, and Moderna which have obtained licenses from the World Health Organization (WHO). However, the discovery of the vaccine was not welcomed by some people. This is because of the post-vaccine impact and the vaccine development period which is considered too short. In this study, sentiment analysis was carried out based on public sentiment on Twitter social media about the covid-19 vaccine that has obtained a license from WHO uses NLP (Natural Language Processing) and machine learning algorithms. The purpose of this research is to find out the sentiment circulating on Twitter towards WHO-certified vaccines such as Pfizer, Moderna and AstraZeneca based on NLP as decision makers and sources of reference for the general public. Based on the research results, the highest positive sentiment was the Pfizer vaccine then Moderna, namely 47.30% and 46.20%. Meanwhile, the AstraZeneca vaccine received the lowest sentiment rating of the three, namely 40.09%.
Co-Authors Iphang Prayoga Primandani Arsi