ANALYSIS OF INDONESIAN SOCIETY'S SENTIMENT ON THE 2019 CORONAVIRUS (COVID-19) VACCINE ON TWITTER SOCIAL MEDIA USING LONG SHORT-TERM MEMORY (LSTM) ALGORITHM

Wahyu Syilawah, Dhymas (2022) ANALYSIS OF INDONESIAN SOCIETY'S SENTIMENT ON THE 2019 CORONAVIRUS (COVID-19) VACCINE ON TWITTER SOCIAL MEDIA USING LONG SHORT-TERM MEMORY (LSTM) ALGORITHM. ["eprint_fieldopt_thesis_type_tugasakhir" not defined] thesis, University of Technology Yogyakarta.

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Abstract

ABSTRACT The COVID-19 vaccination program triggered public reaction and attention, both positive, negative, and neutral opinions, which eventually became a hot topic of conversation among the people of Indonesia. Due to the limited space for expressing their views, many people express their opinions through social media networks. Twitter is one of the social media that is already popular in discussions and expressing views in the public sphere. The opinions expressed are of various types. There are positive ones, such as supporting the program, and there are negative opinions, such as assuming that the vaccination program is only for the benefit of an organization, group, or individual. Thus, in this study, the author tries to analyze public opinion about the covid-19 virus by classifying the Indonesian people's views. Data collected from the Twitter social media network contains many public sentiments using the Long Short Term Memory (LSTM) algorithm. Furthermore, in this study, the text of public opinion was classified and grouped into positive and negative sentiments. The results of the confusion matrix test get an accuracy value of 79.3%, precision of 80%, and recall of 81%, so it can be concluded that the Long Short Term Memory algorithm can perform sentiment classification.

Item Type:	Thesis (["eprint_fieldopt_thesis_type_tugasakhir" not defined])
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User:	Kaprodi S1 Informatika UTY
Date Deposited:	30 Nov 2022 01:43
Last Modified:	30 Nov 2022 01:43
URI:	http://eprints.uty.ac.id/id/eprint/11252

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