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Mobile Forensics Analysis of Line Messenger on Illegal Drug Transaction Case using National Institute of Standard Technology (NIST) Method

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Aulia Putri Utami, Imam Riadi

Aulia Putri Utami and Imam Riadi. Mobile Forensics Analysis of Line Messenger on Illegal Drug Transaction Case using National Institute of Standard Technology (NIST) Method. International Journal of Computer Applications 183(32):23-33, October 2021. BibTeX

	author = {Aulia Putri Utami and Imam Riadi},
	title = {Mobile Forensics Analysis of Line Messenger on Illegal Drug Transaction Case using National Institute of Standard Technology (NIST) Method},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2021},
	volume = {183},
	number = {32},
	month = {Oct},
	year = {2021},
	issn = {0975-8887},
	pages = {23-33},
	numpages = {11},
	url = {},
	doi = {10.5120/ijca2021921712},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


The rapid development of technology and information every year has caused an increase in the use of social media applications in the world to jump up to 40 percent due to the COVID-19 pandemic. The increase in the use of IM applications is followed by the development of the negative side of the use of technology, one of which is drug transactions. This study makes a simulation for cases of online drug transactions through the LINE service on an Android-based smartphone which is analyzed using the steps recommended by the National Institute of Standards and Technology. Simulation tests were carried out using Magnet AXIOM, Autopsy, and MOBILedit Forensics Express displayed with the DataReader program. Based on the test results, digital evidence in the form of LINE accounts, pictures, phone history, and geo-locations that have been deleted have been successfully recovered with the percentage of discovery using MOBILedit as much as 71%, Autopsy 57%, and Magnet AXIOM 43%. The results of word cloud visualization using text mining in the RStudio application also succeeded in detecting words related to drug cases, namely paket and gorila.


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Forensics, Mobile, LINE, Narcotics, NIST, Wordcloud