Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine

The Indonesian government is attempting to track the spread of the virus by creating an application named “PeduliLindungi” to deal with the coronavirus's exponential increase in cases across the country. Because it has a feature to disclose the user's location immediately, it is envisaged...

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Main Authors: Rizki Rahmatullah, Jundi Nourfateha Elquthb, Fanya Nindha Al-Qurani, Annisa Uswatun Khasanah
Format: Article
Language:English
Published: UIN Sunan Kalijaga, Faculty of Science and Technology, Industrial Engineering Department 2024-08-01
Series:Journal of Industrial Engineering and Halal Industries
Subjects:
Online Access:https://ejournal.uin-suka.ac.id/saintek/JIEHIS/article/view/4672
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author Rizki Rahmatullah
Jundi Nourfateha Elquthb
Fanya Nindha Al-Qurani
Annisa Uswatun Khasanah
author_facet Rizki Rahmatullah
Jundi Nourfateha Elquthb
Fanya Nindha Al-Qurani
Annisa Uswatun Khasanah
author_sort Rizki Rahmatullah
collection DOAJ
description The Indonesian government is attempting to track the spread of the virus by creating an application named “PeduliLindungi” to deal with the coronavirus's exponential increase in cases across the country. Because it has a feature to disclose the user's location immediately, it is envisaged that this program can reduce the transmission of viruses in monitoring. Indonesians have used the PeduliLindungi, and there are user reviews of both positive and negative experiences. Therefore, to enhance these services, an assessment is required. The text mining method can extract information from users' reviews to collect this data. This method's application additionally uses the Naive Bayes Classifier and Support Vector Machine algorithms, which analyze word associations and do a classification evaluation of the data's accuracy. Based on the two methods' calculations, the NBC algorithm's average classification accuracy was 83.81%, and the SVM algorithm was 93.84%. Following that, discoveries on words that frequently exist or are used by people are obtained through word associations in the sentiment analysis of positive or negative reviews.
format Article
id doaj-art-34ed28e281b8427098416d5d557f0520
institution Kabale University
issn 2722-8150
2722-8142
language English
publishDate 2024-08-01
publisher UIN Sunan Kalijaga, Faculty of Science and Technology, Industrial Engineering Department
record_format Article
series Journal of Industrial Engineering and Halal Industries
spelling doaj-art-34ed28e281b8427098416d5d557f05202025-01-06T05:54:18ZengUIN Sunan Kalijaga, Faculty of Science and Technology, Industrial Engineering DepartmentJournal of Industrial Engineering and Halal Industries2722-81502722-81422024-08-0151364210.14421/jiehis.46724296Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector MachineRizki Rahmatullah0Jundi Nourfateha Elquthb1Fanya Nindha Al-Qurani2Annisa Uswatun Khasanah3Universitas Islam IndonesiaUniversitas Islam IndonesiaUniversitas Islam IndonesiaUniversitas Islam IndonesiaThe Indonesian government is attempting to track the spread of the virus by creating an application named “PeduliLindungi” to deal with the coronavirus's exponential increase in cases across the country. Because it has a feature to disclose the user's location immediately, it is envisaged that this program can reduce the transmission of viruses in monitoring. Indonesians have used the PeduliLindungi, and there are user reviews of both positive and negative experiences. Therefore, to enhance these services, an assessment is required. The text mining method can extract information from users' reviews to collect this data. This method's application additionally uses the Naive Bayes Classifier and Support Vector Machine algorithms, which analyze word associations and do a classification evaluation of the data's accuracy. Based on the two methods' calculations, the NBC algorithm's average classification accuracy was 83.81%, and the SVM algorithm was 93.84%. Following that, discoveries on words that frequently exist or are used by people are obtained through word associations in the sentiment analysis of positive or negative reviews.https://ejournal.uin-suka.ac.id/saintek/JIEHIS/article/view/4672classificationnaïve bayes classifierpedulilindungisentiment analysissupport vector machineword association
spellingShingle Rizki Rahmatullah
Jundi Nourfateha Elquthb
Fanya Nindha Al-Qurani
Annisa Uswatun Khasanah
Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine
Journal of Industrial Engineering and Halal Industries
classification
naïve bayes classifier
pedulilindungi
sentiment analysis
support vector machine
word association
title Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine
title_full Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine
title_fullStr Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine
title_full_unstemmed Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine
title_short Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine
title_sort sentiment analysis of pedulilindungi user using naive bayes classifier algorithm and support vector machine
topic classification
naïve bayes classifier
pedulilindungi
sentiment analysis
support vector machine
word association
url https://ejournal.uin-suka.ac.id/saintek/JIEHIS/article/view/4672
work_keys_str_mv AT rizkirahmatullah sentimentanalysisofpedulilindungiuserusingnaivebayesclassifieralgorithmandsupportvectormachine
AT jundinourfatehaelquthb sentimentanalysisofpedulilindungiuserusingnaivebayesclassifieralgorithmandsupportvectormachine
AT fanyanindhaalqurani sentimentanalysisofpedulilindungiuserusingnaivebayesclassifieralgorithmandsupportvectormachine
AT annisauswatunkhasanah sentimentanalysisofpedulilindungiuserusingnaivebayesclassifieralgorithmandsupportvectormachine