Hasil Cek Similarity Mobile Forensics for Cyberbullying Detection using Term Frequency - Inverse Document Frequency (TF-IDF)

Riadi, Imam and Sunardi, Sunardi and WIDIANDANA, PANGGAH (2019) Hasil Cek Similarity Mobile Forensics for Cyberbullying Detection using Term Frequency - Inverse Document Frequency (TF-IDF). JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika), 5 (2). pp. 68-76. ISSN ISSN: 2338-3070

Text HASIL CEK_Imam Riadi, Sunardi, Panggah Widiandana.pdf Download (1MB)

Abstract

The case of cyberbullying in Indonesia was ranked third in the world in 2015 and as much as 91% was experienced by children. RSA Anti-Fraud Command Center (AFCC) report reports that in 2015 45% of transactions were carried out through mobile channels, while 61% of fraud occurred through mobile devices. WhatsApp in July 2019, 1.6 billion users access the WhatsApp messenger every month. The data opens a reference for investigators to better anticipate cybercrime actions that can occur in the WhatsApp application because more users are using the application. In this study using the TF-IDF method in detecting cyberbullying, that occurs to be able to add a reference for investigators. The conclusions that have been obtained from the simulation of conversations between four people in a WhatsApp group get the results of the cyberbullying rate that the user "C" has a cyberbullying rate of 50% from the data proving that the TF-IDF method can help investigators detect someone who will commit cyberbullying actions but in its development, a better way is needed when preprocessing so that the abbreviation or changing words can still be detected perfectly

Item Type:	Artikel Umum
Subjects:	T Technology > T Technology (General)
Divisi / Prodi:	Master (Magister) > Master of Technology Informatica (Magister Teknologi Informatika)
Depositing User:	Dr Imam Riadi
Date Deposited:	17 Dec 2022 08:28
Last Modified:	17 Dec 2022 08:28
URI:	http://eprints.uad.ac.id/id/eprint/38029

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