International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 183 - Number 40 |
Year of Publication: 2021 |
Authors: Suryani, Imam Riadi |
10.5120/ijca2021921798 |
Suryani, Imam Riadi . Web Forensic for Hate Speech Content on Twitter Services using National Institute of Standard Technology Method. International Journal of Computer Applications. 183, 40 ( Dec 2021), 30-38. DOI=10.5120/ijca2021921798
Technological developments in addition to bringing many positive impacts also have negative impacts. The sophistication of various applications today allows the increase in crime cases online. These cases include gambling online, spreading hoax news, fraud, hate speech, cyberbullying, cyberporn, and other cyber cases. These crimes online are very often found in various social media applications, one of which is the Twitter application which is a social networking site that allows users to share things or events that are happening around the world. Users post tweets that can contain photos, videos, links, and text. This research conducts forensics on the Twitter application accessed via the web browser Chrome as the browser with the most users in Indonesia in 2020 according to Stat Counter. The research was conducted using case scenarios based on original cases obtained from various sources. The stages used in this research are the stages from the National Institute of Standards and Technology. These stages are collection, examination, analysis, and reporting. The process of collecting digital evidence is carried out using several forensic tools, namely Belkasoft RAM Capturer, FTK Imager, Browser History Capturer, and Browser History Viewer. This research produces digital evidence in the form of tweets previously deleted or posts that can be retrieved, along with other data. The percentage of results of the digital evidence that has been found successfully 100%.InBelkasoft RAM Capturer and FTK Imager is 50% with digital evidence of text posted, username, password, and web browser history. In Browser History Capturer and Browser History Viewer is 50%with digital evidence of image posted, web browser history, profile photo of the twitter account, and time accessed. The results of this research managed to find evidence of posts that have been deleted.