Pendeteksi Face Mask Menggunakan Model CNN (Convolutional Neural Network)

  • Rivaldi Julian Saputra -
  • Yuliarman Saragih Universitas Singaperbangsa Karawang
  • Arnisa Stefani Universitas Singaperbangsa Karawang

Abstract

Health protocols are needed to prevent the spread of Covid-19. The use of face masks is one of the commonly used health protocols. Checking manually to detect faces that are not wearing masks is a long and tedious job. The basis of this research is Deep Learning which is a high-level, layered, and deep modeling algorithm that is widely applied to computer vision. Computer vision is a branch of computer science that can be used for image classification. Convulsional Neural Network is a deep learning algorithm that has good performance in image classification. Transfer learning is the latest method to speed up training time on datasets and to get better classification performance. This study classifies facial images to distinguish people wearing masks or not using Deep Learning. The system will classify and then give status to people wearing masks or not. This artificial intelligence system or what can be called Artificial Intelligence will help human work. This system can be added to more complex outputs such as opening doors, attendance, screening of people who enter public places that have closed rooms

References

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Published
2023-12-27
How to Cite
Saputra, R., Saragih, Y., & Stefani, A. (2023). Pendeteksi Face Mask Menggunakan Model CNN (Convolutional Neural Network). Jurnal Ilmiah Wahana Pendidikan, 9(24), 600-606. https://doi.org/10.5281/zenodo.10435426