(Korespondensi) Assessing Technique For Mapping Public Response To DKI Jakarta Governor Policy In Handling COVID-19 Pandemic Using SVM BASED Sentiment Analysis

Rintyarna, Bagus Setya and Saputra, Wahyu Nurkholis Hadi and Cahyanto, Triawan Adi and Maulida, Riska Nur (2020) (Korespondensi) Assessing Technique For Mapping Public Response To DKI Jakarta Governor Policy In Handling COVID-19 Pandemic Using SVM BASED Sentiment Analysis. International Applied Science, Indonesia.

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Abstract

Since the coronavirus outbreak or known as COVID-19 spread throughout the
world, especially in Indonesia. The Governor of DKI Jakarta issued several policies to
deal with the spread of COVID-19. However, this policy has become a conversation on
social media such as Youtube. Through audience interaction in the comments column,
giving lots of positive and negative sentiment comments, the audience response is
classified using the sentiment analysis technique of comments to find out which
sentiments are positive, negative, and neutral for each comment. In this study, the data
were taken from news video comments. The method used is the Support Vector Machine
and the selection feature uses the Term Frequency-Inverse Document Frequency (TF�IDF). The data used amounted to 945 Indonesian language comments. Accurate results
obtained by using the addition of a stoplist at the preprocessing stage a

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Item Type:	Peer Review
Keywords/Kata Kunci:	Sentiment Analysis, TF-IDF, Support Vector Machine, Youtube, News.
Subjects:	600 Technology and Applied Science > 620 Engineering
Divisions:	Faculty of Engineering > Department of Informatics Engineering (S1)
Depositing User:	Bagus Setya Rintyarna | bagus.setya@unmuhjember.ac.id
Date Deposited:	19 Jun 2023 01:50
Last Modified:	19 Jun 2023 01:50
URI:	http://repository.unmuhjember.ac.id/id/eprint/17326

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