SISTEM KEAMANAN PINTU RUMAH BERDASARKAN PENGENALAN WAJAH MENGGUNAKAN KAMERA BERBASIS INTERNET OF THINGS

Dhia Assyifa Sabitaswari. “Sistem Keamanan Pintu Rumah Berdasarkan Pengenalan Wajah Berbasis Internet of Things”. Skripsi, Jakarta, Program Studi Pendidikan Teknik Elektronika, Fakultas Teknik, Universitas Negeri Jakarta, 2020. Dosen Pembimbing Dr. W. Djatmiko, MT. dan Drs. Jusuf Bintoro, M.T. Tujuan dari penelitian ini adalah untuk merancang sistem keamanan rumah upaya memberi rasa aman dengan cara menggunakan kamera berbasis Internet of Things sebagai media pendeteksi untuk dapat mendeteksi wajah yang dikenal maupun tidak dikenal oleh sistem di pintu rumah, sehingga membantu pemilik rumah untuk memonitoring siapa saja yang ingin masuk ke dalam rumah dan adanya kemudahan untuk mengakses rumah. Dalam meneliti, merancang dan merealisasikan Sistem Keamanan Pintu Rumah Berdasarkan Pengenalan Wajah Berbasis Internet of Things dilakukan di Laboratorium Elektronika Fakultas Teknik Universitas Negeri Jakarta pada semester ganjil (113) hingga semester ganjil (115) tahun akademik 2020/2021. Penelitian ini dilakukan dengan metode Research and Development, dari 10 langkah penelitian, hanya dilakukan 4 langkah penelitian. Sistem Keamanan Pintu Rumah Berdasarkan Pengenalan Wajah Berbasis Internet of Things direalisasikan terdiri dari 6 sistem : (1) Sensor kamera OV2640 sebagai sensor yang dapat mendeteksi wajah (2) Sistem indikator suara berupa speaker sebagai penerjemah perintah sistem (3) Sistem penguncian pintu berupa solenoid door lock (4) kontroller ESP-32 CAM yang dilengkapi WiFi (5) Sistem keamanan darurat (6) Internet of Things. Sistem Keamanan Pintu Rumah Berdasarkan Pengenalan Wajah Menggunakan Kamera Berbasis Internet of Things sudah berhasil dibuat dan sudah diuji. Sistem sudah didaftarkan tiga ID Wajah dengan masing-masing presentasi keberhasilan pengenalan wajah ID[0] 80%, ID[1] 100%, dan ID[2] 90% lalu solenoid door lock aktif. Blynk menerima notifikasi jika sistem mendeteksi wajah tidak terdaftar dan menampilkan video stream dan dapat membuka kunci dari Blynk dengan akurasi keberhasilan sebesar 100%. Kata kunci : Sistem Keamanan, Pengenalan Wajah, ESP-32 CAM, Kamera OV2640, Internet of Things ABSTRACT Dhia Assyifa Sabitaswari. “Face Recognition-Based Home Door Security System Based on the Internet of Things”. Thesis, Jakarta, Electronics Engineering Education Study Program, Faculty of Engineering, State University of Jakarta. 2021. Supervisors: Dr. W. Djatmiko, MT. and Drs. Jusuf Bintoro, M.T. The purpose of this research is to design a home security system to provide a sense of security by using a camera based on the Internet of Things as a media detector to get detect that face is known nor unknown by di system door of the house, thus helping homeowners to monitor anyone who wants to enter the house and be a convenience to access the house. In researching, designing, and realizing Home Based Door Security System Face Recognition Based on the Internet of Things done at the researcher's house in the odd semester (113) until odd semester (115) academic year 2020/2021. This research was conducted with an engineering method technique. Door Security System Home Based Face Recognition Based on the Internet of Things realized consists of from 6 systems: (1) OV2640 camera sensor as sensors that could detect faces (2) Voice indicator system inform of the speakers as command translator system (3) Door locking system in the form of the solenoid door lock (4) controller ESP-32 CAM which equipped with WiFi (5) Security system emergency (6) the Internet of Things. Door Security System Home Based Face Recognition Based on the Internet of Things realized consists of from 6 systems: (1) OV2640 camera sensor as sensors that could detect faces (2) Voice indicator system inform of the speakers as command translator system (3) Door locking system in the form of the solenoid door lock (4) controller ESP-32 CAM which equipped with WiFi (5) Security system emergency (6) Internet of Things. Door Security System Home Based Face Recognition Based on the Internet of Things has been successfully created and tested. The system has registered three Face IDs with each presentation of facial recognition success ID[0] 80%, ID[1] 100%, and ID[2] 90% then the solenoid is door lock active. Blynk receives a notification if the system detects an unregistered face and displays a video stream and can unlock from Blynk with 100% success accuracy. Keywords: Security Systems, Face Recognition, ESP-32 CAM, Camera OV2640, Internet of Thing