Levels of Political Participation Based on Naive Bayes Classifier
Nowadays, social media is growing rapidly and globally until it finally became an important part of society. During campaign period for the regional head election in Indonesia, the candidates and their supporting parties actively use social media as a campaign tool. Social media like Twitter has bee...
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| Main Authors: | , , , |
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| Format: | EJournal Article |
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IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.,
2019-01-31.
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| Online Access: | Get Fulltext Get Fulltext |
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| LEADER | 02612 am a22003253u 4500 | ||
|---|---|---|---|
| 001 | IJCSS_42531 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Hidayatillah, Rumaisah |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Mirwan, Mirwan |e author |
| 700 | 1 | 0 | |a Hakam, Mohammad |e author |
| 700 | 1 | 0 | |a Nugroho, Aryo |e author |
| 245 | 0 | 0 | |a Levels of Political Participation Based on Naive Bayes Classifier |
| 260 | |b IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., |c 2019-01-31. | ||
| 500 | |a https://jurnal.ugm.ac.id/ijccs/article/view/42531 | ||
| 520 | |a Nowadays, social media is growing rapidly and globally until it finally became an important part of society. During campaign period for the regional head election in Indonesia, the candidates and their supporting parties actively use social media as a campaign tool. Social media like Twitter has been known as a political microblogging media that can provide data about current political event based on users' tweets. By using Twitter as a data source, this study analyzes public participation during campaign period for 2018 Central Java regional head election. The purpose is to observe how much reaction is given to each candidate who advanced in the election. By using the crawling program, all tweets containing certain candidate names will be downloaded. After going through a series of preprocessing stages, data can be classified using Naive Bayes. Predictor features in classification datasets are the number of replies, retweets, and likes. While the target variable is reaction that is divided into three levels, including high, medium, and low. These levels are determined based on users' reaction in a tweet. By using these rules, Naive Bayes managed to classify data correctly as much as 76.74% for Ganjar Pranowo and 68.81% for Sudirman Said. | ||
| 540 | |a Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems) | ||
| 540 | |a http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Informatics Engineering | ||
| 690 | |a social media; election campaign; naïve bayes | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 73-82 | |
| 786 | 0 | |n 2460-7258 | |
| 786 | 0 | |n 1978-1520 | |
| 787 | 0 | |n https://jurnal.ugm.ac.id/ijccs/article/view/42531/23721 | |
| 856 | 4 | 1 | |u https://jurnal.ugm.ac.id/ijccs/article/view/42531 |z Get Fulltext |
| 856 | 4 | 1 | |u https://jurnal.ugm.ac.id/ijccs/article/view/42531/23721 |z Get Fulltext |