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Journal : IJoICT (International Journal on Information and Communication Technology)

WhatsApp Chat Visualizer: A Visualization of WhatsApp Messenger’s Artifact Using the Timeline Method Hardiansyah Shidek; Niken Cahyani; Aulia Arif Wardana
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 1 (2020): June 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.61.489

Abstract

WhatsApp is a medium that everyone can use to interact and to share information effectively and efficiently. However, it can be misused for criminal activities. Analyzing WhatsApp' artifacts is quite challenging as the suspect may have a lot of random conversational data to be considered. This makes it difficult for the trial process to obtain digital traces that can be identified in malicious activities such as knowing who was involved when the conversation was held and the timespan. Therefore, in this research, a social media investigation of WhatsApp was carried out by acquiring data from rooted Android devices that were used as target devices for forensic activities. A python-based application is developed to show the content of the conversation, and a web-based application is presented to visualize the data using the Timeline method. Experimental results in this research display important timeline information such as information about who was involved when and what time the conversation was carried out with the suspect.
Non-Line of Sight LoRa –Based Localization using RSSI-Kalman-Filter and Trilateration Thirafi Wian Anugrah; Andrian Rakhmatsyah; Aulia Arif Wardana
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 2 (2020): December 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.00.495

Abstract

The method that analyzes in this research is the combination of the Received Signal Strength Indicator (RSSI) with the Trilateration Method. This research also filtered the RSSI value using the Kalman filter method for smoothing data. The localization system traditionally based on Global Positioning System (GPS) device. However, GPS technology not working well in Non-line-of-sight (NLOS) like an indoor location or mountain area. The other way to implement the localization system is by using LoRa technology. This technology used radio frequency to communicate with each other node. The radiofrequency has a measurement value in the form of signal strength. These parameters, when combined with the trilateration method, can be used as a localization system. After implementation and testing, the system can work well compared with the GPS system for localization. RMSE is used to calculate error distance on these methods, the result from three methods used, the value from RSSI with Kalman filter have a close result to actual position, then value GPS follows with close result from Kalman filter, and the last one is RSSI without Kalman filter.