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An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm

Aware on the benefits of social media as the networking platform, the extremist organization is utilized social media to spread the ideology, recruit new member and guided a suicide bomber alike. There are opportunities to analyze the content of document texts in social media including the terrorism...

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Main Authors: Aryuni, Mediana, Miranda, Eka, Fernando, Yudi, Kibtiah, Tia Mariatul
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2020
Subjects:
HD28 Management. Industrial Management
T Technology (General)
Online Access:http://umpir.ump.edu.my/id/eprint/42441/1/An%20early%20warning%20detection%20system%20of%20terrorism%20in%20Indonesia.pdf
http://umpir.ump.edu.my/id/eprint/42441/2/An%20early%20warning%20detection%20system%20of%20terrorism%20in%20Indonesia%20from%20Twitter%20contents%20using%20na%C3%AFve%20bayes%20Algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42441/
https://doi.org/10.1109/ICIMTech50083.2020.9211261
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spelling my.ump.umpir.424412024-12-02T01:12:10Z http://umpir.ump.edu.my/id/eprint/42441/ An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm Aryuni, Mediana Miranda, Eka Fernando, Yudi Kibtiah, Tia Mariatul HD28 Management. Industrial Management T Technology (General) Aware on the benefits of social media as the networking platform, the extremist organization is utilized social media to spread the ideology, recruit new member and guided a suicide bomber alike. There are opportunities to analyze the content of document texts in social media including the terrorism detection and intention by extracting the content evident in their post, comment etc. The objective of this research is to analyze content posted in Twitter and to review whether post and conversation on Twitter will be highly related to terrorism intention or another way around. This study deployed Naïve Bayes classification technique which identified Twitter contents in Indonesian national language. The method has been processed text pre-processing, and dataset divided with hold out technique. Result of F-measure value indicates that 76% and 77% of texts are associated with the accuracy level of terrorism based on macro-averaging and micro-averaging indicators. The finding is contributed to the scanty literature on the early warning detection method in Indonesian language and assist the government to target the extremists' organizations. Institute of Electrical and Electronics Engineers Inc. 2020-08 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42441/1/An%20early%20warning%20detection%20system%20of%20terrorism%20in%20Indonesia.pdf pdf en http://umpir.ump.edu.my/id/eprint/42441/2/An%20early%20warning%20detection%20system%20of%20terrorism%20in%20Indonesia%20from%20Twitter%20contents%20using%20na%C3%AFve%20bayes%20Algorithm_ABS.pdf Aryuni, Mediana and Miranda, Eka and Fernando, Yudi and Kibtiah, Tia Mariatul (2020) An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm. In: Proceedings of 2020 International Conference on Information Management and Technology, ICIMTech 2020. 5th International Conference on Information Management and Technology, ICIMTech 2020 , 13 - 14 August 2020 , Virtual, Bandung. pp. 555-559. (9211261). ISBN 978-172817071-8 (Published) https://doi.org/10.1109/ICIMTech50083.2020.9211261
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic HD28 Management. Industrial Management
T Technology (General)
spellingShingle HD28 Management. Industrial Management
T Technology (General)
Aryuni, Mediana
Miranda, Eka
Fernando, Yudi
Kibtiah, Tia Mariatul
An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm
description Aware on the benefits of social media as the networking platform, the extremist organization is utilized social media to spread the ideology, recruit new member and guided a suicide bomber alike. There are opportunities to analyze the content of document texts in social media including the terrorism detection and intention by extracting the content evident in their post, comment etc. The objective of this research is to analyze content posted in Twitter and to review whether post and conversation on Twitter will be highly related to terrorism intention or another way around. This study deployed Naïve Bayes classification technique which identified Twitter contents in Indonesian national language. The method has been processed text pre-processing, and dataset divided with hold out technique. Result of F-measure value indicates that 76% and 77% of texts are associated with the accuracy level of terrorism based on macro-averaging and micro-averaging indicators. The finding is contributed to the scanty literature on the early warning detection method in Indonesian language and assist the government to target the extremists' organizations.
format Conference or Workshop Item
author Aryuni, Mediana
Miranda, Eka
Fernando, Yudi
Kibtiah, Tia Mariatul
author_facet Aryuni, Mediana
Miranda, Eka
Fernando, Yudi
Kibtiah, Tia Mariatul
author_sort Aryuni, Mediana
title An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm
title_short An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm
title_full An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm
title_fullStr An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm
title_full_unstemmed An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm
title_sort early warning detection system of terrorism in indonesia from twitter contents using naïve bayes algorithm
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2020
url http://umpir.ump.edu.my/id/eprint/42441/1/An%20early%20warning%20detection%20system%20of%20terrorism%20in%20Indonesia.pdf
http://umpir.ump.edu.my/id/eprint/42441/2/An%20early%20warning%20detection%20system%20of%20terrorism%20in%20Indonesia%20from%20Twitter%20contents%20using%20na%C3%AFve%20bayes%20Algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42441/
https://doi.org/10.1109/ICIMTech50083.2020.9211261
_version_ 1822924758347415552
score 13.235318

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