Cyberbullying Analysis on Instagram Using K-Means Clustering

Social Media, in addition to having a positive impact on society, also has a negative effect. Based on statistics, 95 percent of internet users in Indonesia use the internet to access social networks. Especially for young people, Instagram is more widely used than other social media such as Twitter...

Full description

Saved in:
Bibliographic Details
Published in:Juita : jurnal informatika (Online) Vol. 10; no. 2; pp. 261 - 271
Main Authors: Muhariya, Ahmad, Riadi, Imam, Prayudi, Yudi
Format: Journal Article
Language:English
Indonesian
Published: Universitas Muhammadiyah Purwokerto 14.11.2022
Subjects:
clustering
cyberbullying
instagram
kmeans
social media
ISSN:2086-9398, 2579-8901
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Social Media, in addition to having a positive impact on society, also has a negative effect. Based on statistics, 95 percent of internet users in Indonesia use the internet to access social networks. Especially for young people, Instagram is more widely used than other social media such as Twitter and Facebook. In terms of cyberbullying cases, cases often occur through social media, Twitter, and Instagram. Several methods are commonly used to analyze cyberbullying cases, such as SVM (Support Vector Machine), NBC (Naïve Bayes Classifier), C45, and K-Nearest Neighbors. Application of a number of these methods is generally implemented on Twitter social media. Meanwhile, young users currently use Instagram more social media than Twitter. For this reason, the research focuses on analyzing cyberbullying on Instagram by applying the K-Mean Clustering algorithm. This algorithm is used to classify cyberbullying actions contained in comments. The dataset used in this study was taken from 2019 to 2021 with 650 records; there were 1827 words and already had labels. This study has successfully classified the tested data with a threshold value of 0.5. The results for grouping words containing bullying on Instagram resulted in the highest accuracy, which is 67.38%, a precision value of 76.70%, and a recall value of 67.48%. These results indicate that the k-means algorithm can make a grouping of comments into two clusters: bullying and non-bullying.
AbstractList Social Media, in addition to having a positive impact on society, also has a negative effect. Based on statistics, 95 percent of internet users in Indonesia use the internet to access social networks. Especially for young people, Instagram is more widely used than other social media such as Twitter and Facebook. In terms of cyberbullying cases, cases often occur through social media, Twitter, and Instagram. Several methods are commonly used to analyze cyberbullying cases, such as SVM (Support Vector Machine), NBC (Naïve Bayes Classifier), C45, and K-Nearest Neighbors. Application of a number of these methods is generally implemented on Twitter social media. Meanwhile, young users currently use Instagram more social media than Twitter. For this reason, the research focuses on analyzing cyberbullying on Instagram by applying the K-Mean Clustering algorithm. This algorithm is used to classify cyberbullying actions contained in comments. The dataset used in this study was taken from 2019 to 2021 with 650 records; there were 1827 words and already had labels. This study has successfully classified the tested data with a threshold value of 0.5. The results for grouping words containing bullying on Instagram resulted in the highest accuracy, which is 67.38%, a precision value of 76.70%, and a recall value of 67.48%. These results indicate that the k-means algorithm can make a grouping of comments into two clusters: bullying and non-bullying.
Author Prayudi, Yudi
Riadi, Imam
Muhariya, Ahmad
Author_xml – sequence: 1
  givenname: Ahmad
  surname: Muhariya
  fullname: Muhariya, Ahmad
– sequence: 2
  givenname: Imam
  surname: Riadi
  fullname: Riadi, Imam
– sequence: 3
  givenname: Yudi
  surname: Prayudi
  fullname: Prayudi, Yudi
BookMark eNo9kMtqwzAQRUVJoWmaH-jKP-BUb0vQTTB9hKZ006yFJI-DgmMXyS747-s6pZuZuXfgLM4tWrRdCwjdE7xhWGjxcBpCbzffBAe6IZxrfIWWVBQ6VxqTxXRjJXPNtLpB65ROGGNKuRSMLtFjOTqIbmiaMbTHbNvaZkwhZV2b7drU22O05-yQfn9v-TvYNmVlM6Qe4lTdoevaNgnWf3uFDs9Pn-Vrvv942ZXbfe6JYDgXhGJQwLwgBETNHZbAFJmmrviUvONa-krUIKCiDKwC50B5iaUqlBVshXYXbtXZk_mK4WzjaDobzFx08Whs7INvwAjhPS2qwtHacq-4k9aDZLoqCuHqQk8semH52KUUof7nEWxmnWbWaWadZtbJfgBrAGwJ
ContentType Journal Article
DBID AAYXX
CITATION
DOA
DOI 10.30595/juita.v10i2.14490
DatabaseName CrossRef
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
DatabaseTitleList
CrossRef
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 2579-8901
EndPage 271
ExternalDocumentID oai_doaj_org_article_55cc27d7b2fa4c84b6ace639d775bf79
10_30595_juita_v10i2_14490
GroupedDBID AAYXX
ADBBV
ALMA_UNASSIGNED_HOLDINGS
BCNDV
CITATION
GROUPED_DOAJ
ID FETCH-LOGICAL-c1530-5120e8e3c511e5f4b06e38106e9d44b0cb496cd5fe5ed23ea8ebbe8c606878a53
IEDL.DBID DOA
ISSN 2086-9398
IngestDate Fri Oct 03 12:33:04 EDT 2025
Sat Nov 29 02:20:43 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 2
Language English
Indonesian
License http://creativecommons.org/licenses/by/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c1530-5120e8e3c511e5f4b06e38106e9d44b0cb496cd5fe5ed23ea8ebbe8c606878a53
OpenAccessLink https://doaj.org/article/55cc27d7b2fa4c84b6ace639d775bf79
PageCount 11
ParticipantIDs doaj_primary_oai_doaj_org_article_55cc27d7b2fa4c84b6ace639d775bf79
crossref_primary_10_30595_juita_v10i2_14490
PublicationCentury 2000
PublicationDate 2022-11-14
PublicationDateYYYYMMDD 2022-11-14
PublicationDate_xml – month: 11
  year: 2022
  text: 2022-11-14
  day: 14
PublicationDecade 2020
PublicationTitle Juita : jurnal informatika (Online)
PublicationYear 2022
Publisher Universitas Muhammadiyah Purwokerto
Publisher_xml – name: Universitas Muhammadiyah Purwokerto
SSID ssj0002246532
ssib051604975
Score 2.200598
Snippet Social Media, in addition to having a positive impact on society, also has a negative effect. Based on statistics, 95 percent of internet users in Indonesia...
SourceID doaj
crossref
SourceType Open Website
Index Database
StartPage 261
SubjectTerms clustering
cyberbullying
instagram
kmeans
social media
Title Cyberbullying Analysis on Instagram Using K-Means Clustering
URI https://doaj.org/article/55cc27d7b2fa4c84b6ace639d775bf79
Volume 10
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 2579-8901
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002246532
  issn: 2086-9398
  databaseCode: DOA
  dateStart: 20100101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 2579-8901
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssib051604975
  issn: 2086-9398
  databaseCode: M~E
  dateStart: 20100101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LS8NAEF5EPHjxLdYXe_Ama9Nkn-BFi0UQiweF3sI-JtBSWqltwX_v7CaV3Lx4zLKE8M1kvxl25htCbqzqgS18YEjGwLgMkjnX4wxy56tgpKl8PWxCDYd6NDJvrVFfsSaslgeugesK4X2ugnJ5ZbnX3EnrAWk1KCVcpVLrHkY9rWQKPUn0JEa-DTFOkshL1BGLVwq4WTJTGF130KC7G9GdrDARv1v3snEebzvjAd1iqZaYf2KdwQHZa8JF-lB_5iHZGocjsr8ZxUCbP_OY3Pe_XQRoOo1tS3QjNULnMxrLAWyswaKpPIC-sFdAfqL96SqKJODSCfkYPL33n1kzGIF5PKAyxDXPQEPhMVoCUXGXSYhKXRJM4PjkHTfSB1GBgJAXYDU4B9pjsqKVtqI4Jduz-QzOCDXKZNIqgVGD4c5ytI0MKhjnQp4F4TvkdgNE-VnrX5SYNyTYygRbmWArE2wd8hix-t0ZtavTAlq0bCxa_mXR8_94yQXZzWOjQizY45dke7lYwRXZ8evl-GtxnZzlB4eTwsc
linkProvider Directory of Open Access Journals
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Cyberbullying+Analysis+on+Instagram+Using+K-Means+Clustering&rft.jtitle=Juita+%3A+jurnal+informatika+%28Online%29&rft.au=Ahmad+Muhariya&rft.au=Imam+Riadi&rft.au=Yudi+Prayudi&rft.date=2022-11-14&rft.pub=Universitas+Muhammadiyah+Purwokerto&rft.issn=2086-9398&rft.eissn=2579-8901&rft.volume=10&rft.issue=2&rft.spage=261&rft.epage=271&rft_id=info:doi/10.30595%2Fjuita.v10i2.14490&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_55cc27d7b2fa4c84b6ace639d775bf79
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2086-9398&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2086-9398&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2086-9398&client=summon