Automatic Door Access Model Based on Face Recognition using Convolutional Neural Network
DOI:
https://doi.org/10.30812/matrik.v22i1.2350Keywords:
Automatic door access, Amason face recognition, Convolutional Neural Network, Facial recognition, RaspberryAbstract
Automatic door access technology by utilizing biometrics such as fingerprints, retinas and facial structures is constantly evolving. The use of masks during the Covid-19 Pandemic and post-pandemic has become an obligation wherever humans are active. The study aimed to create an automated door access model using Convolutional Neural Network (CNN) algorithms and Amazon Rekognition as cloud-based software. The CNN algorithm is applied to classify faces wearing masks or not wearing masks. The CNN architecture model uses sequential, convolution2D, max polling 2D, flatten dan dense. The hardware includes the Raspberry Pi, USB Webcam, Relay, and Magnetic Doorlock. The test results were obtained from the results of the accuracy plot on the Convolutional Neural Network model with an accuracy rate of 99% at an epoch value of 8 with a learning time of 67 seconds.
Downloads
Download data is not yet available.
References
[1] M. Abdillah, S. Rasyad, and N. Alfarizal, “Implementasi Sistem Pendeteksi Penggunaan Masker Berbasis Raspberry Pi 4 Menggunakan Metode Convolution Neural Network (CNN) pada Proses Screening Protokol Kesehatan COVID-19,†Ijccs, vol. 6, no. 1, pp. 1–5, 2022.
[2] M. Abdul, R. Irham, and D. A. Prasetya, “Prototipe Pendeteksi Masker Pada Ruangan Wajib Masker untuk Kendali Pintu Otomatis Berbasis Deep Learning Sebagai Pencegahan Penularan Covid-19,†Prototipe Pendeteksi Masker Pada Ruangan Wajib Masker Untuk Kendali Pintu Otomatis Berbasis Deep Learning Sebagai Pencegahan Penularan Covid-19, pp. 47–55, 2020.
[3] H. W. N. Agusti and B. A. Gisela, “Pengenalan Wajah dengan Menggunakan Smartphone : Sistematik Review,†Journal of Indonesian Forensic and Legal Medicine, vol. 2, no. 2, pp. 156–163, 2020.
[4] A. Apriani, H. Zakiyudin, and K. Marzuki, “Penerapan Algoritma Cosine Similarity dan Pembobotan TF-IDF System Penerimaan Mahasiswa Baru pada Kampus Swasta,†Jurnal Bumigora Information Technology (BITe), vol. 3, no. 1, pp. 19–27, 2021, doi: 10.30812/bite.v3i1.1110.
[5] I. F. Ashari, M. D. Satria, and M. Idris, “Parking System Optimization Based on IoT using Face and Vehicle Plat Recognition via Amazon Web Service and ESP-32 CAM,†Computer Engineering and Applications Journal, vol. 11, no. 2, pp. 137–153, 2022, doi: 10.18495/comengapp.v11i2.409.
[6] M. F. Aslan, K. Sabanci, A. Durdu, and M. F. Unlersen, “COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization,†Computers in Biology and Medicine, 2020.
[7] M. N. Baay, A. N. Irfansyah, and M. Attamimi, “Sistem Otomatis Pendeteksi Wajah Bermasker Menggunakan Deep Learning,†Jurnal Teknik ITS, vol. 10, no. 1, pp. 64–70, Aug. 2021, doi: 10.12962/j23373539.v10i1.59790.
[8] A. H. Bachtiar, P. P. Surya, and R. P. Astutik, “Rancang Bangun Dual Keamanan Sistem Pintu Rumah Menggunakan Pengenalan Wajah dan Sidik Jari Berbasis Iot (Internet of Things),†Jurnal POLEKTRO: Jurnal Power Elektronik, vol. 1, no. 1, pp. 102–107, 2022.
[9] A. D, “Face Recognition using Machine Learning Algorithms,†JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, vol. 14, no. 3, Jun. 2019, doi: 10.26782/jmcms.2019.06.00017.
[10] P. Elechi, E. Okowa, and U. Ekwueme, “Facial Recognition Based Smart Door Lock System,†FUPRE Journal of Scientific and Industrial Research, vol. 6, no. 2, pp. 95–105, 2022.
[11] A. Febriansyah, J. Saputra, and P. Desvirati, “Alat Pendeteksi Suhu Tubuh dan Wajah (Kebutuhan Bukti Kehadiran) Berbasis Data,†Manutech : Jurnal Teknologi Manufaktur, vol. 14, no. 01, pp. 1–6, 2022.
[12] Gaurav Dhiman, Srihari. K, Ramesh. R, and Udayakumar. E, “An Innovative Approach for Face Recognition Using Raspberry Pi,†Artificial Intelligence Evolution, vol. 10, no. 1, pp. 102–107, Aug. 2020, doi: 10.37256/aie.12202062.
[13] H. Hairani, A. S. Suweleh, and D. Susilowaty, “Penanganan Ketidak Seimbangan Kelas Menggunakan Pendekatan Level Data,†MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 20, no. 1, pp. 109–116, 2020, doi: 10.30812/matrik.v20i1.846.
[14] A. Hassouneh, A. M. Mutawa, and M. Murugappan, “Development of a Real-Time Emotion Recognition System Using Facial Expressions and EEG based on machine learning and deep neural network methods,†Informatics in Medicine Unlocked, vol. 20, no. 1, pp. 2–9, 2020, doi: 10.1016/j.imu.2020.100372.
[15] S. E. Oltean, “Mobile Robot Platform with Arduino Uno and Raspberry Pi for Autonomous Navigation,†Procedia Manufacturing, vol. 32, pp. 572–577, 2019, doi: 10.1016/j.promfg.2019.02.254.
[16] R. R. Ramdhani, R. I. Adam, and A. A. Ridha, “Implementasi Deep Learning Untuk Deteksi Masker Deep Learning Implementation for Face Mask Detection,†Journal of Information Technology and Computer Science (INTECOMS), vol. 4, no. 2, p. 2021, 2021.
[2] M. Abdul, R. Irham, and D. A. Prasetya, “Prototipe Pendeteksi Masker Pada Ruangan Wajib Masker untuk Kendali Pintu Otomatis Berbasis Deep Learning Sebagai Pencegahan Penularan Covid-19,†Prototipe Pendeteksi Masker Pada Ruangan Wajib Masker Untuk Kendali Pintu Otomatis Berbasis Deep Learning Sebagai Pencegahan Penularan Covid-19, pp. 47–55, 2020.
[3] H. W. N. Agusti and B. A. Gisela, “Pengenalan Wajah dengan Menggunakan Smartphone : Sistematik Review,†Journal of Indonesian Forensic and Legal Medicine, vol. 2, no. 2, pp. 156–163, 2020.
[4] A. Apriani, H. Zakiyudin, and K. Marzuki, “Penerapan Algoritma Cosine Similarity dan Pembobotan TF-IDF System Penerimaan Mahasiswa Baru pada Kampus Swasta,†Jurnal Bumigora Information Technology (BITe), vol. 3, no. 1, pp. 19–27, 2021, doi: 10.30812/bite.v3i1.1110.
[5] I. F. Ashari, M. D. Satria, and M. Idris, “Parking System Optimization Based on IoT using Face and Vehicle Plat Recognition via Amazon Web Service and ESP-32 CAM,†Computer Engineering and Applications Journal, vol. 11, no. 2, pp. 137–153, 2022, doi: 10.18495/comengapp.v11i2.409.
[6] M. F. Aslan, K. Sabanci, A. Durdu, and M. F. Unlersen, “COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization,†Computers in Biology and Medicine, 2020.
[7] M. N. Baay, A. N. Irfansyah, and M. Attamimi, “Sistem Otomatis Pendeteksi Wajah Bermasker Menggunakan Deep Learning,†Jurnal Teknik ITS, vol. 10, no. 1, pp. 64–70, Aug. 2021, doi: 10.12962/j23373539.v10i1.59790.
[8] A. H. Bachtiar, P. P. Surya, and R. P. Astutik, “Rancang Bangun Dual Keamanan Sistem Pintu Rumah Menggunakan Pengenalan Wajah dan Sidik Jari Berbasis Iot (Internet of Things),†Jurnal POLEKTRO: Jurnal Power Elektronik, vol. 1, no. 1, pp. 102–107, 2022.
[9] A. D, “Face Recognition using Machine Learning Algorithms,†JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, vol. 14, no. 3, Jun. 2019, doi: 10.26782/jmcms.2019.06.00017.
[10] P. Elechi, E. Okowa, and U. Ekwueme, “Facial Recognition Based Smart Door Lock System,†FUPRE Journal of Scientific and Industrial Research, vol. 6, no. 2, pp. 95–105, 2022.
[11] A. Febriansyah, J. Saputra, and P. Desvirati, “Alat Pendeteksi Suhu Tubuh dan Wajah (Kebutuhan Bukti Kehadiran) Berbasis Data,†Manutech : Jurnal Teknologi Manufaktur, vol. 14, no. 01, pp. 1–6, 2022.
[12] Gaurav Dhiman, Srihari. K, Ramesh. R, and Udayakumar. E, “An Innovative Approach for Face Recognition Using Raspberry Pi,†Artificial Intelligence Evolution, vol. 10, no. 1, pp. 102–107, Aug. 2020, doi: 10.37256/aie.12202062.
[13] H. Hairani, A. S. Suweleh, and D. Susilowaty, “Penanganan Ketidak Seimbangan Kelas Menggunakan Pendekatan Level Data,†MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 20, no. 1, pp. 109–116, 2020, doi: 10.30812/matrik.v20i1.846.
[14] A. Hassouneh, A. M. Mutawa, and M. Murugappan, “Development of a Real-Time Emotion Recognition System Using Facial Expressions and EEG based on machine learning and deep neural network methods,†Informatics in Medicine Unlocked, vol. 20, no. 1, pp. 2–9, 2020, doi: 10.1016/j.imu.2020.100372.
[15] S. E. Oltean, “Mobile Robot Platform with Arduino Uno and Raspberry Pi for Autonomous Navigation,†Procedia Manufacturing, vol. 32, pp. 572–577, 2019, doi: 10.1016/j.promfg.2019.02.254.
[16] R. R. Ramdhani, R. I. Adam, and A. A. Ridha, “Implementasi Deep Learning Untuk Deteksi Masker Deep Learning Implementation for Face Mask Detection,†Journal of Information Technology and Computer Science (INTECOMS), vol. 4, no. 2, p. 2021, 2021.
Downloads
Published
2022-11-30
Issue
Section
Articles
How to Cite
[1]
T. A. Zuraiyah, S. Maryana, and A. Kohar, “Automatic Door Access Model Based on Face Recognition using Convolutional Neural Network”, MATRIK, vol. 22, no. 1, pp. 241–258, Nov. 2022, doi: 10.30812/matrik.v22i1.2350.
Similar Articles
- Michael Michael, Frenky Tanoto, Eric Wibowo, Frenky Lutan, Abdi Dharma, Pengenalan Plat Kendaraan Bermotor dengan Menggunakan Metode Template Matching dan Deep Belief Network , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 1 (2019)
- Wahyu Riski Aulia Putra, Agus Reza Aristiadi Nurwa, Dimas Febriyan Priambodo, Muhammad Hasbi, Infrastructure as Code for Security Automation and Network Infrastructure Monitoring , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 1 (2022)
- Imam Riadi, Abdul Fadlil, Muhammad Amirul Mu'min, OWASP Framework-based Network Forensics to Analyze the SQLi Attacks on Web Servers , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
- Ismail Husein, Rina Widyasari, Algorithm Symmetric 2-DLDA for Recognizing Handwritten Capital Letters , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 2 (2022)
- Edi Ismanto, Januar Al Amien, Vitriani Vitriani, A Comparison of Enhanced Ensemble Learning Techniques for Internet of Things Network Attack Detection , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 3 (2024)
- Lathifatul Mahabbati, Andy Hidayat Jatmika, Raphael Bianco Huwae, Reducing Transmission Signal Collisions on Optimized Link State Routing Protocol Using Dynamic Power Transmission , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Lalu Zazuli Azhar Mardedi, Ariyanto Ariyanto, Analisa Kinerja System Gluster FS pada Proxmox VE untuk Menyediakan High Availability , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 1 (2019)
- Irawan Afrianto, Andri Heryandi, Sufa Atin, Blockchain-based Trust, Transparent, Traceable Modeling on Learning Recognition System Kampus Merdeka , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Imam Fahrur Rozi, Ahmadi Yuli Ananta, Endah Septa Sintiya, Astrifidha Rahma Amalia, Yuri Ariyanto, Arin Kistia Nugraeni, Analyzing the Application of Optical Character Recognition: A Case Study in International Standard Book Number Detection , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 2 (2025)
- Yunanri W, Ammar Fauzan, Ahmad Yani, Muhammad Abdul Aziz, Analisis Performance Central Prosessing Unit (CPU) Realtime Menggunakan Metode Benchmarking , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
You may also start an advanced similarity search for this article.
.png)
