Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Sistem Informasi dan Informatika
I Wayan Desta Gafatia
Universitas Bina Darma
Computer Science & IT Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analisis Pro Kontra Vaksin Covid 19 Menggunakan Sentiment Analysis Sumber Media Sosial Twitter I Wayan Desta Gafatia; Novri Hadinata
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 2 No. 1 (2021): Jurnal Pengembangan Sistem Informasi & Informatika
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v2i1.544

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.
Co-Authors Hadinata, Novri