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Optimization Sentimen Analysis using CRISP-DM and Naive Bayes Methods Implemented on Social Media

Cyberspace: Jurnal Pendidikan Teknologi Informasi · Vol. 6 No. 2 (2022) · hlm. 74–85

DOI
10.22373/cj.v6i2.12793
ISSN
2597-9671, 2598-2079
Terbit
2022-10-29
Penerbit
Universitas Islam Negeri Ar-Raniry Banda Aceh
Bahasa
eng

Abstrak

Freedom of expression on social media Twitter not always give positive value, because sometimes can contains negative things such as fake news, spreads hate speech, and racism, where these kinds of tweet can be categorized as an act of Cyberbullying. Where this cyberbullying tends to increase every time. The aim of this study is to use the Naïve Bayes method in classifying types of sentiment on Twitter. The keyword used is Saipul Jamil, and the tweet was taken in September 2021. A total of 18,067 tweets were collected and then they will be labelled with a positive or negative value. This study also uses the CRIPS-DM method which is consist of Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment stages. The results of this study obtained the value of Accuracy (85.6%), Negative Recall (82.1%), Positive Recall (90.23%), and Negative Precision (91.76%) Positive Precision (79.18%).

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  • Universitas Budi Luhur
  • State University of Semarang
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Rahmat NugrohoAfiliasi tidak diketahui1
Catur NugrohoState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://jurnal.ar-raniry.ac.id/index.php/cyberspace/oai, pertama di-harvest 7 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Optimization Sentimen Analysis using CRISP-DM and Naive Bayes Methods Implemented on Social Media</dc:title>
	<dc:creator xml:lang="en">Kurniawan, Denni</dc:creator>
	<dc:creator xml:lang="en">Yasir, Muhammad</dc:creator>
	<dc:subject xml:lang="en">Cyberbullying</dc:subject>
	<dc:subject xml:lang="en">CRIPS-DM</dc:subject>
	<dc:subject xml:lang="en">Naïve Bayes</dc:subject>
	<dc:subject xml:lang="en">Sentiment Analysis</dc:subject>
	<dc:subject xml:lang="en">Twitter</dc:subject>
	<dc:description xml:lang="en">Freedom of expression on social media Twitter not always give positive value, because sometimes can contains negative things such as fake news, spreads hate speech, and racism, where these kinds of tweet can be categorized as an act of Cyberbullying. Where this cyberbullying tends to increase every time. The aim of this study is to use the Naïve Bayes method in classifying types of sentiment on Twitter. The keyword used is Saipul Jamil, and the tweet was taken in September 2021. A total of 18,067 tweets were collected and then they will be labelled with a positive or negative value. This study also uses the CRIPS-DM method which is consist of Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment stages. The results of this study obtained the value of Accuracy (85.6%), Negative Recall (82.1%), Positive Recall (90.23%), and Negative Precision (91.76%) Positive Precision (79.18%).</dc:description>
	<dc:publisher xml:lang="en">Universitas Islam Negeri Ar-Raniry Banda Aceh</dc:publisher>
	<dc:date>2022-10-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.ar-raniry.ac.id/index.php/cyberspace/article/view/12793</dc:identifier>
	<dc:identifier>10.22373/cj.v6i2.12793</dc:identifier>
	<dc:source xml:lang="en">Cyberspace: Jurnal Pendidikan Teknologi Informasi; Vol. 6 No. 2 (2022); 74-85</dc:source>
	<dc:source xml:lang="id">CYBERSPACE: Jurnal Pendidikan Teknologi Informasi; Vol 6 No 2 (2022); 74-85</dc:source>
	<dc:source>2597-9671</dc:source>
	<dc:source>2598-2079</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jurnal.ar-raniry.ac.id/index.php/cyberspace/article/view/12793/7503</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2022 Denni Kurniawan</dc:rights>
</oai_dc:dc>