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Vol. 5 No. 3 (2024) • Articles
Open Access

Perbandingan Kinerja Model Pre-Trained CNN (VGG16, RESNET, dan INCEPTIONV3) untuk Aplikasi Pengenalan Wajah pada Sistem Absensi Karyawan

Muhammad Khatama Insani
Universitas Stikubank
Dwi Budi Santoso
Universitas Stikubank
Published: September 20, 2024 Pages: 2612-2622
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Abstract

Face recognition has become a key technology in improving the efficiency and security of modern employee attendance systems. This study compares the performance of three pre-trained Convolutional Neural Network (CNN) models - VGG16, ResNet50, and InceptionV3 - in the context of face recognition for employee attendance systems. The study evaluated the accuracy, consistency, and generalization of the models on a dataset of employee faces, using prediction accuracy, confusion matrix, and classification report measurement methods. Results showed InceptionV3 performed best overall, with high consistency and confidence, achieving up to 99% accuracy on the test data. ResNet50 showed consistent performance in some cases but required further fine-tuning, while VGG16 showed the worst performance. These findings have significant practical implications for the industry, recommending the use of InceptionV3 for the implementation of reliable face recognition-based attendance systems, with consideration of the use of confidence thresholds to optimize accuracy. This research also highlights the importance of further optimization, including hyperparameter fine-tuning and more sophisticated data augmentation strategies, to improve system performance under various work environment conditions.

Keywords:
Facial Recognition Convolutional Neural Network (CNN) Employee Attendance System Model Comparison
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Author Biographies
Muhammad Khatama Insani Universitas Stikubank

Fakultas Teknologi Informasi dan Industri, Universitas Stikubank, Kota Semarang, Provinsi Jawa Tengah, Indonesia.

Dwi Budi Santoso Universitas Stikubank

Fakultas Teknologi Informasi dan Industri, Universitas Stikubank, Kota Semarang, Provinsi Jawa Tengah, Indonesia.

How to Cite
Insani, M. K., & Santoso, D. B. (2024). Perbandingan Kinerja Model Pre-Trained CNN (VGG16, RESNET, dan INCEPTIONV3) untuk Aplikasi Pengenalan Wajah pada Sistem Absensi Karyawan. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(3), 2612-2622. https://doi.org/10.35870/jimik.v5i3.925
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References
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