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 <titleInfo>
  <title>Sentiment Analysis on the Ratification of Penghapusan Kekerasan Seksual Bill on Twitter</title>
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  <namePart>Hamidi Gary Dimitri</namePart>
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  <place>
   <placeTerm type="text">Bandung</placeTerm>
   <publisher>Maranatha University Press</publisher>
   <dateIssued>2021</dateIssued>
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  <languageTerm type="text">Indonesia</languageTerm>
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  <form authority="gmd">Artikel Jurnal</form>
  <extent>hlm : 655-665</extent>
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  <title>JUTISI : Jurnal Teknik Informatika dan Sistem Informasi</title>
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<note>&#13;
Abstract&#13;
Rancangan Undang-Undang Penghapusan Kekerasan Seksual (RUU PKS), or the bill of the Republic of Indonesia on the Elimination of Sexual Violence, is a bill that discusses sexual violence, victim protection and its scope concern the matters related to sexual violence. Elimination of sexual violence according to the PKS Bill aims to prevent all forms of violence. These discussions and conversations also occur on social media, especially on Twitter. Taking public sentiment is significant in choosing the proper messages, interference, and policy. Sentiment analysis is a field of study that analyses opinions, sentiments, judgments, evaluations of a person attitudes and emotions regarding a particular topic, service, product, individual, organization or activity. This study used the method of crawling to get data from Twitter. Then data cleansing, data processing is carried out using Bernoulli, Logistic Regression, and Support Vector Classification (SVC) algorithm. The data is then evaluated using three methods: accuracy, classification report, and confusion matrix. Based on the three algorithms used, it is found that all methods are equally accurate with 0.65. This study found positive, negative, and neutral sentiments expressed to the bill of Elimination of Sexual Violence through comments. It is shown that most people using the keyword “RUU PKS” are positive to the bill of Elimination of Sexual Violence (RUU PKS) while most people’s sentiments using #RUUPKSBukanSolusi are negative to the bill.&#13;
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<subject authority="">
 <topic>Informatika</topic>
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<subject authority="">
 <topic>Sistem Informasi</topic>
</subject>
<classification>JUTISI</classification>
<identifier type="isbn">24432210</identifier>
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 <physicalLocation>Perpustakaan Teknik UPI YAI </physicalLocation>
 <shelfLocator>JUTISI V7N3 Desember 2021</shelfLocator>
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   <sublocation>Perpustakaan FT UPI YAI</sublocation>
   <shelfLocator>JUTISI V7N3 Desember 2021</shelfLocator>
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