<![CDATA[Bullying is an unpleasant behavior that makes someone feel uncomfortable, hurt, and emotionally and psychologically distressed. One form of bullying that often goes undetected is verbal bullying, which is not directly visible but has a profound impact on the victim. This research aims to prevent verbal bullying by utilizing AI technology in campus and school environments. This research uses a qualitative method with a case study approach, which focuses on in-depth exploration of specific contexts and phenomena, allowing researchers to understand in detail how AI can detect verbal bullying. AI will be used to analyze conversations in the context of classes and other social interactions, with the ability to recognize language patterns containing elements of sarcasm, insults, or bullying behavior that are difficult for humans to see. While the technology is promising, a key challenge is the AI's ability to understand the nuances of human behavior, such as sarcasm or different cultural contexts, which can affect detection accuracy. In addition, the use of AI in these sensitive environments raises ethical issues related to privacy, which need to be carefully addressed. The data collection technique was conducted with a questionnaire given to 572 respondents consisting of students, teachers, lecturers, and education personnel in Sumedang Regency. The data analysis technique used the Miles and Huberman model, which includes three stages: data reduction, data presentation, and conclusion drawing. The results of the analysis show that the utilization of AI to detect verbal bullying in school and campus environments is very potential, but human supervision is still needed to verify the results of AI detection.]]>
Copyrights © 2025
