Mengukur Pengalaman Pengguna Aplikasi MochiMochi Menggunakan User Experiment Quisioner - Novi Novi; Hendrick Hendrick (Institut Teknologi dan Bisnis (ITB) Semarang, 2026)
Automatic facial expression recognition is a significant challenge in human-computer interaction with broad relevance in mental health, security, and behavioral analysis. This study proposes the implementation of Deep Learning using a custom Convolutional Neural Network (CNN) architecture to classify seven basic emotion categories: angry, disgust, fear, happy, sad, surprise, and neutral. Key challenges such as lighting variations and visual feature ambiguity in the FER2013 dataset are addressed through image pre-processing techniques, data augmentation, and the use of Batch Normalization and Dropout layers to prevent overfitting. The research methodology involves a systematic architectural design with three main convolution blocks optimized for computational efficiency. Experimental results show that the proposed model achieved a validation accuracy of 68.2%. Performance analysis based on F1-Score reveals that the