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All Journal International Journal of Advances in Intelligent Informatics
Sasuwuk, James Rio
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Computer Science & IT

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Pattern recognition for facial expression detection using convolution neural networks Pusadan, Mohammad Yazdi; Sasuwuk, James Rio; Pratama, Septiano Anggun; Laila, Rahma
International Journal of Advances in Intelligent Informatics Vol 11, No 4 (2025): November 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i1.1602

Abstract

The COVID-19 pandemic was a devastating disaster for humanity worldwide. All aspects of life were disrupted, including daily activities and education. The education sector faced significant challenges at all levels, from kindergarten to elementary, junior high, and high school, as well as in higher education, where learning had to be online. Human emotions are primarily conveyed through facial expressions resulting from facial muscle movements. Facial expressions serve as a form of nonverbal communication, reflecting a person’s thoughts and emotions. This research aims to classify emotions based on facial expressions using the Convolutional Neural Network (CNN) and detect faces using the Viola-Jones method in video recordings of online meetings. We utilize the VGG-16 architecture, which consists of 16 layers, including convolutional layers with the ReLU activation function and pooling layers, specifically max pooling. The fully connected layer also employs the ReLU activation function, while the output layer uses the Softmax. The Viola-Jones method is used for facial detection in images, achieving an accuracy of 87.6% in locating faces. Meanwhile, the CNN method is applied for facial expression recognition, with an accuracy of 59.8% in classifying emotions.
Co-Authors Laila, Rahma Mohammad Yazdi Pusadan Septiano Anggun Pratama