<![CDATA[Cyberbullying on instant messaging platforms such as WhatsApp is a serious problem due to its psychological impact on victims and the difficulty of obtaining valid digital evidence. This study aims to analyze and uncover digital evidence of cyberbullying in WhatsApp groups using digital forensic methods based on the National Institute of Standards and Technology (NIST) framework, which includes the stages of collection, examination, analysis, and reporting. The research object was simulated WhatsApp conversation data obtained through a logical acquisition process on an Android device. Acquisition and analysis were performed using the digital forensic tools Autopsy, SQLite Viewer, and Cellebrite UFED. The research stages were carried out by simulating a cyberbullying case, and the simulation results were then acquired using the NIST stages. The data studied in the group consisted of 243 messages. The results showed that the NIST method was able to identify important digital artifacts in the form of conversation databases and user metadata, as well as reveal 77 messages containing elements of cyberbullying, consisting of 39 verbal insults, 25 taunts, and 14 derogatory comments. Data integrity verification was performed using SHA-256 hash values, which showed consistency before and after the extraction process, thus fulfilling the principle of forensic soundness. These findings prove that the application of NIST-based digital forensic methods is effective in supporting cyberbullying investigations on WhatsApp groups and is relevant for use in academic, legal, and cybersecurity contexts.]]>
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