Digital Forensic Investigates Sexual Harassment on Telegram using Naïve Bayes

Authors

  • Meyti Eka Apriyani Politeknik Negeri Malang, Indonesia
  • Rahmad Alfian Maskuri Politeknik Negeri Malang, Indonesia
  • Muhammad Hasyim Ratsanjani Politeknik Negeri Malang, Indonesia
  • Agung Nugroho Pramudhita Politeknik Negeri Malang, Indonesia
  • Rawansyah Rawansyah Politeknik Negeri Malang, Indonesia

DOI:

10.33395/sinkron.v8i3.12514

Keywords:

Forensic, Investigation, Method, Naïve Bayes, Telegram

Abstract

The widespread use of Telegram in Indonesia has had both positive and negative effects. While the app offers strong security features, it has also become a platform for digital crimes, including sexual harassment. This study aims to address the need for effective forensic analysis and classification methods by employing the National Institute of Justice (NIJ) methodology and Naïve Bayes classifier to analyze conversations on Telegram. The research evaluates the performance of digital forensic tools and the effectiveness of the Naïve Bayes method in identifying instances of sexual harassment conversation. The data analyzed is about conversations on the telegram application that contain sexual harassment.  Data collection involves extracting relevant conversations and subjecting them to forensic analysis using MOBIL edit Forensic Express and FTK Imager. Based on the test results, the naïve Bayes algorithm can be used to classify conversations into positive and negative about sexual harassment. The value obtained from naïve Bayes testing is the accuracy value of 91.3%, Precision 100%, and Recall 90%.

 

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How to Cite

Apriyani, M. E. ., Maskuri, R. A. ., Ratsanjani, M. H. ., Pramudhita, A. N. ., & Rawansyah, R. (2023). Digital Forensic Investigates Sexual Harassment on Telegram using Naïve Bayes. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(3), 1409-1417. https://doi.org/10.33395/sinkron.v8i3.12514

Issue

Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023

Section

Articles

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Copyright (c) 2023 Meyti Meyti, Rahmad Alfian Maskuri, Muhammad Hasyim Ratsanjani, Agung Nugroho Pramudhita, Rawansyah Rawansyah

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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