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Timotius Selar Sitompul
Universitas Negeri Medan
Humanities Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences Transportation

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Pengenalan Ekspresi Wajah Menggunakan Convolutional Neural Network (CNN) Richard Steven Immanuel Sihombing; Rafif Nauval Tuah Siregar; Vijay Sitorus; Timotius Selar Sitompul
Journal of Creative Student Research Vol. 1 No. 6 (2023): Desember : Journal of Creative Student Research
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jcsrpolitama.v1i6.3046

Abstract

Facial expression recognition is an important research area in the advancement of machine learning. This research uses Convolutional Neural Network (CNN) as a method for recognizing facial expressions with a fairly high level of accuracy. This research uses a dataset obtained from Kaggle in the form of images of facial expressions, including surprised, happy, sad, afraid, angry and neutral. The MobilenetV2 CNN model was trained and tested using this dataset. The research results show that the model is able to recognize facial expressions with 78% accuracy on test data. It can be concluded that the MobilenetV2 model is quite capable of recognizing facial expressions.
Co-Authors Rafif Nauval Tuah Siregar Richard Steven Immanuel Sihombing Vijay Sitorus