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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Fachmi Ramdani
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Computer Science & IT

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Identifikasi text mining isu blokir Kominfo di Twitter dengan metode support vertor machine Fachmi Ramdani
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3323

Abstract

The increasingly widespread use of social media has led to the formation of a forum that can be used by the public to express opinions in various forms, one of which is the use of Twitter. One of the issues that is currently being discussed is related to public opinion re-garding the Blocking of Communications and Informatics that arose as a result of the gov-ernment blocking applications that had not been registered with the Indonesian Communi-cations and Information Technology's Electronic System Operator (PSE), which was a trending topic on various social media platforms, one of which was Twitter. This study aims to analyze the various comments on Twitter given by the public. Collecting data from this study uses several approaches, one of which is taking data from keywords and hashtags with a certain amount of data that can be classified, then after the data is collect-ed it will go through a data processing process using the text mining method. Support Vec-tor Machine (SVM) Algorithm. This research will obtain a system that can classify positive and negative comments.
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