Deteksi Ekspresi Wajah Dalam Upaya Pencegahan Bullying Menggunakan Framework Tensor Flow dan Java Script Berbasis Website

Abstract

Facial expressions are changes in facial appearance that occur in response to a person's emotions, intentions, and social interactions. Facial expression analysis is an important research area because facial expressions serve as a non-verbal communication tool commonly used by humans to convey emotions, feelings, and social messages in everyday life. In many bullying cases, facial expressions may not accurately represent an individual's true emotional state. Some individuals may appear happy on the outside while internally experiencing sadness, anxiety, or intense emotional distress. Therefore, facial expression detection is needed to accurately identify emotional states and support bullying prevention efforts. This study proposes a web-based facial expression detection system for bullying prevention using TensorFlow and JavaScript. The system is expected to provide accurate recognition of human emotions and feelings, enabling appropriate interventions and effective solutions for handling bullying cases. The research utilizes TensorFlow, an open-source machine learning library, along with JavaScript to recognize and classify seven basic human facial expressions, including happiness, sadness, anger, fear, surprise, disgust, and contempt, as well as a neutral expression. By accurately identifying emotional conditions, the proposed system is expected to contribute to more effective bullying prevention and support a safer social environment.