Implementasi Sistem Keamanan Rumah Berbasis Pengenalan Wajah untuk Peningkatan Keamanan Residensial
DOI:
https://doi.org/10.29408/jit.v7i1.23868Keywords:
ESP32CAM, Internet of Things, Face Recognation, Door, Safety SystemAbstract
The objective of this research is to develop a home security system that utilizes facial recognition technology using the Haar Cascade method and ESP32CAM. In the face of criminal threats, the importance of an effective home security system is increasing. The facial recognition method employed in this study is the Haar Cascade method, which utilizes specific facial features to identify individual identities. The ESP32CAM sensor is used as a camera to capture facial images of the home occupants. The research involves the process of collecting facial image data from the home occupants, which is then used to train the facial recognition model. Subsequently, the model is implemented in a home security system that is connected to the internet and equipped with motion sensors. When motion is detected, the ESP32CAM camera captures an image of the visitor's face and compares it with the previously identified facial data. If a match is found, the system grants access to the visitor. The research results demonstrate that the developed home security system achieves accurate facial recognition with a high success rate. Therefore, this system has the potential to enhance home security and provide better protection for its occupants
References
B. M. Susanto, F. E. Purnomo, and M. F. I. Fahmi, “Sistem Keamanan Pintu Berbasis Pengenalan Wajah Menggunakan Metode Fisherface,” J. Ilm. Inov., vol. 17, no. 1, 2017, doi: 10.25047/jii.v17i1.464.
W. Sulaeman, E. Alimudin, A. Sumardiono, P. N. Cilacap, T. Elekronika, and K. Cilacap, “Sistem Pengaman Loker dengan Menggunakan Deteksi Wajah,” J. Energy Electr. Eng., vol. 3, no. 2, pp. 117–122, 2022.
N. A. Setiawan and H. Huseini, “Simulasi Pengenalan Wajah Untuk Membuka Miniatur Pintu Menggunakan Metode Local Binary Pattern (Lbp) Dan Arduino Uno,” J. Infomedia, vol. 1, no. 2, pp. 11–16, 2016, doi: 10.30811/.v1i2.328.
F. L. Ramadini and E. Haryatmi, “Penggunaan Metode Haar Cascade Classifier dan LBPH Untuk Pengenalan Wajah Secara Realtime,” InfoTekJar J. Nas. Inform. dan Teknol. Jar., vol. 6, no. 2, pp. 1–8, 2022, [Online]. Available: https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/4714/pdf
R. Hariani and N. Fadillah, “Deteksi Kehadiran Mahasiswa Secara Realtime Menggunakan Webcam dengan metode Viola Jones,” InfoTekJar (Jurnal Nas. Inform. dan Teknol. Jaringan), vol. 3, no. 2, pp. 151–154, 2019, doi: 10.30743/infotekjar.v3i2.1030.
C.- Di Politeknik and P. Indonesia, “Penerapan Algoritma Viola-Jones Untuk Deteksi Masker,” J. Tek. Inform. dan Sist. Inf., vol. 8, no. 4, pp. 2030–2040, 2021.
R. A. Pahlevi and B. Setiaji, “Analysis of Application Haar Cascade Classifier and Local Binary Pattern Histogram Algorithm in Recognizing Faces With Real-Time Grayscale Images Using Opencv,” J. Tek. Inform., vol. 4, no. 1, pp. 179–186, 2023, doi: 10.52436/1.jutif.2023.4.1.491.
M. Ibrahim and B. Sugiarto, “Rancang Bangun Rumah Pintar (Smart Home) Berbasis Internet Of Things (IoT),” Infotek J. Inform. dan Teknol., vol. 6, no. 1, pp. 1–10, 2023, doi: 10.29408/jit.v6i1.5365.
I. Ady Saputro, “Forensika Citra Digital Untuk Menganalisis Kecocokan Objek Menggunakan Metode SIFT,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 4, pp. 3170–3179, 2022, doi: 10.35957/jatisi.v9i4.2758.
M. F. Wajdi and J. Sugiantara, “DOI : 10.29408/jit.v1i2.903,” Infotk J. Inform. dan Teknol., vol. 1, no. 2, pp. 96–106, 2018.
E. Fadly, S. Adi Wibowo, and A. Panji Sasmito, “Sistem Keamanan Pintu Kamar Kos Menggunakan Face Recognition Dengan Telegram Sebagai Media Monitoring Dan Controlling,” JATI (Jurnal Mhs. Tek. Inform., vol. 5, no. 2, pp. 435–442, 2021, doi: 10.36040/jati.v5i2.3796.
D. D. Darmansah, N. W. Wardani, and M. Y. Fathoni, “Perancangan Absensi Berbasis Face Recognition Pada Desa Sokaraja Lor Menggunakan Platform Android,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 8, no. 1, pp. 91–104, 2021, doi: 10.35957/jatisi.v8i1.629.
M. Harahap, “Deteksi objek manusia pada image dengan metode Thinning nerdasarkan local maxima,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 7, no. 3, pp. 617–627, 2020, doi: 10.35957/jatisi.v7i3.370.
A. I. Pradana, “Deteksi Ketepatan Pengunaan Masker Wajah dengan Algoritma CNN dan Haar Cascade,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 3, pp. 2305–2316, 2022, doi: 10.35957/jatisi.v9i3.2912.
H. Susilawati, A. Rukmana, and F. Nuraeni, “Absensi Karyawan Menggunakan Deteksi Wajah Dan,” vol. 10, no. 1, 2023.
D. Kurnianto, A. M. Hadi, and E. Wahyudi, “Perancangan Sistem Kendali Otomatis pada Smart Home menggunakan Modul Arduino Uno,” J. Nas. Tek. Elektro, vol. 5, no. 2, 2016, doi: 10.20449/jnte.v5i2.276.
M. F. Wicaksono and M. D. Rahmatya, “Implementasi Arduino dan ESP32 CAM untuk Smart Home,” J. Teknol. dan Inf., vol. 10, no. 1, pp. 40–51, 2020, doi: 10.34010/jati.v10i1.2836.
A. W. Wibowo, A. Karima, Wiktasari, A. Yobioktabera, and S. Fahriah, “Pendeteksian dan Pengenalan Wajah Pada Foto Secara Real Time Dengan Haar Cascade dan Local Binary Pattern Histogram,” JTET (Jurnal Tek. Elektro Ter., vol. Vol. 9 No., pp. 6 – 11, 2020.
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