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Forensic Browser on Line Messenger Services for Handling Cyberfraud using National Institute of Standard Technology Method

by Mifthahul Jannah, Imam Riadi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 30
Year of Publication: 2021
Authors: Mifthahul Jannah, Imam Riadi

Mifthahul Jannah, Imam Riadi . Forensic Browser on Line Messenger Services for Handling Cyberfraud using National Institute of Standard Technology Method. International Journal of Computer Applications. 183, 30 ( Oct 2021), 9-16. DOI=10.5120/ijca2021921682

@article{ 10.5120/ijca2021921682,
author = { Mifthahul Jannah, Imam Riadi },
title = { Forensic Browser on Line Messenger Services for Handling Cyberfraud using National Institute of Standard Technology Method },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2021 },
volume = { 183 },
number = { 30 },
month = { Oct },
year = { 2021 },
issn = { 0975-8887 },
pages = { 9-16 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2021921682 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T01:18:17.732322+05:30
%A Mifthahul Jannah
%A Imam Riadi
%T Forensic Browser on Line Messenger Services for Handling Cyberfraud using National Institute of Standard Technology Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 30
%P 9-16
%D 2021
%I Foundation of Computer Science (FCS), NY, USA

Advances in information and communication technology play an important role in everyday life which is useful for interacting with one another. each other and make it easier for humans to do some work. Line Messenger is an online chat application that sends a text message in real-time, in addition to text messages, other features of the Line messenger application are audio files, videos, and also photos or images using the internet network with the number of users reaching 217 million in 2016. Cyberfraud is a new type of fraud that uses modern cyber information technology, and its essence is still a fraud crime. This study will use a scenario about the Cyberfraud case from a conversation using an instant messenger application, namely Line which runs on the Chrome web browser using the NIST (National Institute of Standards and Technology) stages. This study uses several forensic tools in finding the digital evidence needed including namely FTK Imager, Belkasoft, Browser History Capturer, Browser History Viewer, and Browser History Examination. Digital evidence found in Belkasoft and FTK Imager was 60% with digital evidence of conversation text, Email, and account ID. In Browser History Capturer andBrowser History Viewer as much 40% with digital evidence Photos and Links. Furthermore on Browser History Capturer and Browser History Examiner tools as much as 40% with digital evidence in the form of Links and Cached Web.

  1. D. A. González-Padilla and L. Tortolero-Blanco, “Social media influence in the COVID-19 pandemic,” Int. Braz J Urol, vol. 46, no. Suppl 1, pp. 120–124, 2020, doi: 10.1590/S1677-5538.IBJU.2020.S121.
  2. A. Yudhana, I. Riadi, and I. Zuhriyanto, “Analisis Live Forensics Aplikasi Media Sosial Pada Browser Menggunakan Metode Digital Forensics Research Workshop (DFRWS),” J. TECHNO, vol. 20, no. 2, pp. 125–130, 2019.
  3. A. Fauzan, I. Riadi, and A. Fadlil, “Analisis Forensik Digital Pada Line Messenger Untuk Penanganan Cybercrime,” Annu. Res. Semin., vol. 2, no. 1, pp. 159–163, 2017, [Online]. Available:
  4. D. T. Yuwono, A. Fadlil, and S. Sunardi, “Performance Comparison of Forensic Software for Carving Files using NIST Method,” J. Teknol. dan Sist. Komput., vol. 7, no. 3, pp. 89–92, 2019, doi: 10.14710/jtsiskom.7.3.2019.89-92.
  5. M. Fitriana, K. A. AR, and J. M. Marsya, “Penerapana Metode National Institute of Standars and Technology (Nist) Dalam Analisis Forensik Digital Untuk Penanganan Cyber Crime,” Cybersp. J. Pendidik. Teknol. Inf., vol. 4, no. 1, p. 29, 2020, doi: 10.22373/cj.v4i1.7241.
  6. R. A. Bintang, R. Umar, and A. Yudhana, “Analisis Media Sosial Facebook Lite dengan tools Forensik menggunakan Metode NIST,” Techno (Jurnal Fak. Tek. Univ. Muhammadiyah Purwokerto), vol. 21, no. 2, p. 125, 2020, doi: 10.30595/techno.v21i2.8494.
  7. G. H. A. Kusuma and Y. Fadhilah, “Analisis Forensik Digital E-Commerce pada Website Rental Mobil Menggunakan Metode NIST,” Pros. Semin. Nas. SISFOTEK, vol. 3, no. 1, pp. 228–234, 2019.
  8. M. A. Aziz, I. Riadi, and R. Umar, “Alanisis Forensik Line Messenger Berbasis WEB Menggunakan Framework National Institute of Justice (NIJ),” Semin. Nas. Inform. 2018 (semnasIF 2018), vol. 2018, no. November, pp. 51–57, 2018.
  9. M. I. Syahib, I. Riadi, and R. Umar, “Analisis Forensik Digital Aplikasi Beetalk untuk Penanganan Cybercrime Menggunakan Metode NIST,” Semin. Nas. Inform., vol. 2018, no. November, p. 134, 2018, [Online]. Available:
  10. F. Daryabar, M. H. Tadayon, A. Parsi, and H. Sadjadi, “Automated analysis method for forensic investigation of cloud applications on Android,” 2016 8th Int. Symp. Telecommun. IST 2016, pp. 145–150, 2017, doi: 10.1109/ISTEL.2016.7881799.
  11. D. Hariyadi, H. Wijayanto, and I. D. Sari, “Analisis Barang Bukti Digital Aplikasi Paziim Pada Ponsel Cerdas Android Dengan Pendekatan Logical Acquisition,” Cybersecurity dan Forensik Digit., vol. 2, no. 2, pp. 1–5, 2019.
  12. R. Umar and Sahiruddin, “Metode Nist Untuk Analisis Forensik Bukti Digital Pada Perangkat Android,” Pros. SENDU_U_2019, pp. 978–979, 2019.
  13. I. Riadi, A. Yudhana, M. Caesar, and F. Putra, “1490-Article Text-2859-1-10-20190413,” Akuisisi Bukti Digit. Pada Instagram Messenger Berbas. Android Menggunakan Metod. Natl. Inst. Justice, vol. 4, pp. 219–227, 2018.
  14. E. Akbal, F. Güneş, and A. Akbal, “Digital Forensic Analyses of Web Browser Records,” J. Softw., vol. 11, no. 7, pp. 631–637, 2016, doi: 10.17706/jsw.11.7.631-637.
  15. R. Saputra and I. Riadi, “Forensic Browser of Twitter based on Web Services,” Int. J. Comput. Appl., vol. 175, no. 29, pp. 34–39, 2020, doi: 10.5120/ijca2020920832.
  16. P. W. Setyaningsih, Y. Prayudi, and B. Sugiantoro, “Manajemen Bukti Digital Hasil Akuisisi Dfxml,” J. Tek. Inform., vol. 11, no. 1, pp. 47–54, 2018, doi: 10.15408/jti.v11i1.6680.
  17. A. N. Ichsan and I. Riadi, “Mobile Forensic on Android-based IMO Messenger Services using Digital Forensic Research Workshop (DFRWS) Method,” Int. J. Comput. Appl., vol. 174, no. 18, pp. 34–40, 2021, doi: 10.5120/ijca2021921076.
  18. M. Alghizzawi, “The role of digital marketing in consumer behavior: A survey Want more papers like this? The role of digital marketing in consumer behavior: A survey,” Int. J. Inf. Technol. Lang. Stud., vol. 3, no. 1, pp. 24–31, 2019, [Online]. Available:
  19. M. R. Setyawan, A. Yudhana, and A. Fadlil, “Identifikasi Bukti Digital Skype Di Smartphone Android Dengan Metode National Institute Of Justice ( NIJ ),” Semnastek, pp. 565–570, 2019.
  20. F. Iqbal, B. C. M. Fung, M. Debbabi, R. Batool, and A. Marrington, “Wordnet-Based Criminal Networks Mining for Cybercrime Investigation,” IEEE Access, vol. 7, pp. 22740–22755, 2019, doi: 10.1109/ACCESS.2019.2891694.
  21. W. Naro, A. Syatar, M. M. Amiruddin, I. Haq, A. Abubakar, and C. Risal, “Shariah assessment toward the prosecution of cybercrime in indonesia,” Int. J. Criminol. Sociol., vol. 9, no. 1, pp. 572–586, 2020, doi: 10.6000/1929-4409.2020.09.56.
  22. P. Mali, J. S. Sodhi, T. Singh, and S. Bansal, “Analysing the awareness of cyber crime and designing a relevant framework with respect to cyber warfare: An empirical study,” Int. J. Mech. Eng. Technol., vol. 9, no. 2, pp. 110–124, 2018.
  23. M. T. Whitty, “Predicting susceptibility to cyber-fraud victimhood,” J. Financ. Crime, vol. 26, no. 1, pp. 277–292, 2019, doi: 10.1108/JFC-10-2017-0095.
  24. Z. Li, H. Zhang, M. Masum, H. Shahriar, and H. Haddad, “Cyber fraud prediction with supervised machine learning techniques,” ACMSE 2020 - Proc. 2020 ACM Southeast Conf., pp. 176–180, 2020, doi: 10.1145/3374135.3385296.
  25. T. Pandela and I. Riadi, “Browser Forensics on Web-based Tiktok Applications,” Int. J. Comput. Appl., vol. 175, no. 34, pp. 47–52, 2020, doi: 10.5120/ijca2020920897.
Index Terms

Computer Science
Information Sciences


Cyberfraud Line Messenger NIST Forensics Browser