Jonathan Crystal Galle Oppier Primary Author mixed material bibliography BEKASI Universitas Satya Negara Indonesia 2025 id Indonesia

Text

This research aims to design and implement a home security system based on facial recognition that is capable of working in real-time and integrated with the Internet of Things (IoT), in order to overcome the limitations of conventional security systems that are not yet able to detect and respond to potential threats automatically and still rely on manual supervision. The system was developed using an ESP32-CAM module with a Local Binary Pattern Histogram (LBPH) algorithm for the facial identification process, and is integrated with a buzzer and the Telegram application as a two-layer warning system. The method used is prototyping with an iterative approach for two months through direct testing in a residential environment. The test results show that the system is able to recognize faces with 95.42% accuracy, provides a fast response, and works stably in various lighting conditions. The conclusion of this research shows that the system is effective, economical, and can be implemented without major changes to the building structure. This system also shows potential for further development on a more complex smart home scale. Jonathan Crystal Galle Oppier Teknik Informatika Home Security Facial Recognition LBPH ESP32-CAM Telegram, IoT TI 2025 Institutional Repository USNI Universitas Satya Negara Indonesia TI 2025 8250236 Perpustakaan USNI Kampus B (SKRIPSI) TI 2025 IMPLEMENTASI SISTEM KEAMANAN RUMAH BERBASIS FACE RECOGNITION DENGAN PERINGATAN ALARM OTOMATIS MENGGUNAKAN METODE LOCAL BINARY PATTERNS HISTOGRAM 4289 2025-09-17 13:54:18 2025-09-18 14:26:39 machine generated