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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Journal of Innovation and Applied Technology Jurnal Penelitian Pendidikan IPA (JPPIPA)
Suci Astutik
Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Education Materials Science & Nanotechnology Mathematics Physics

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Journal : Jurnal Penelitian Pendidikan IPA (JPPIPA)

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Fuzzy Sugeno Method for Opinion Classification Regarding Policy of PPKM and Covid-19 Vaccination Djihan Wahyuni; Eni Sumarminingsih; Suci Astutik
Jurnal Penelitian Pendidikan IPA Vol. 8 No. 5 (2022): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v8i5.1958

Abstract

The Indonesian government has implemented various interventions to overcome the impact of the Covid-19 pandemic, including those written in Minister of Home Affairs Instructions on PPKM (Community Activities Restrictions Enforcement) and Covid-19 vaccination policies. This policy are not at least reaping the pros and cons, so it is necessary to monitor public opinion to be able to provide solutions or become an evaluation of future policies. The aim of this study is to determine the polarity of public opinion regarding PPKM and Covid-19 vaccinations policies on Twitter, as well as to determine the implementation of FIS Sugeno in classifying textual data. There are several stages carried out, i.e. data collection, data pre-processing, data labeling, data weighting, identification of membership functions, determination of fuzzy sets, formation of a classification system, and evaluation of classification results. In this study, the performance of FIS Sugeno in classifying tweets was quite good with an average accuracy of 89.13%. Meanwhile, public opinion regarding the PPKM and Covid-19 vaccination policies tends to be balanced with 36.92% of tweets classified as a positive sentiments, 22.85% being negative sentiments, and another 40.23% belonging to neutral sentiments.
Co-Authors Darmanto Darmanto Diego Irsandy Djihan Wahyuni Elok Pratiwi Fahimah Fauwziyah Henny Pramoedyo Ismi Chai Runnisa Nisa Dwirahma Widhiasih Sumarminingsih, Eni Theresia Mitakda, Maria Bernadetha Wulaida Rizky Fitrilia