ADITIYA, AFRI (2024) PERANCANGAN ALAT SISTEM OTOMATISASI PINTU GERBANG MENGGUNAKAN ALGORITMA YOLOv3 BERBASIS MIKROPROSESOR DAN MIKROKONTROLER DI UNIVERSITAS MERCU BUANA. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
In today's technological era, optical recognition systems have become a major concern in various fields, especially in access management. This study focuses on the development of an intelligent system for facial recognition and card reading to improve the security and efficiency of access management, especially at the main gate of Mercu Buana University. The integration of computer vision technologies such as Real-Time object Detection with the YOLOv3 algorithm and the use of RFID for card reading provides a robust automation solution for gate access, ensuring that only authorized individuals can enter. This study describes the design and implementation of an automatic gate system using YOLOv3 and RFID, demonstrating its effectiveness in overcoming security challenges and improving access management in a university campus environment. This study uses an experimental method to develop a facial recognition and card reading system at the main gate of Mercu Buana University. The method includes video data capture using a webcam for object Detection with the YOLOv3 algorithm, as well as the use of RFID for card reading. Data is processed using Visual Studio Code and Arduino IDE with Grayscale techniques and median filters for image Processing. System evaluation using Confusion Matrix shows good accuracy, precision, and recall. This study implements a Gate Automation system with the YOLO algorithm and RFID at Mercu Buana University. YOLOv3 successfully detects faces in RealTime and RFID ensures access only for authorized persons. Evaluation with Confusion Matrix shows the accuracy of Detection. The results indicate improved security and access management on campus. Suggestions include the development of YOLOv3 algorithms, exploration of 3D image Processing technology, and further research on data security and integration with other security technologies. Keywords: Gateway, YOLOv3, RFID, Real-Time Object Detection, Confusion Matrix. Di era teknologi saat ini, sistem pengenalan optik telah menjadi perhatian utama di berbagai bidang, terutama dalam manajemen akses. Penelitian ini fokus pada pengembangan sistem cerdas untuk pengenalan wajah dan pembacaan kartu guna meningkatkan keamanan dan efisiensi manajemen akses, khususnya di pintu gerbang utama Universitas Mercu Buana. Integrasi teknologi visi komputer seperti deteksi objek Real-Time dengan algoritma YOLOv3 dan penggunaan RFID untuk pembacaan kartu memberikan solusi otomatisasi yang kuat untuk akses gerbang, memastikan hanya individu yang diizinkan yang dapat masuk. Studi ini mendeskripsikan desain dan implementasi sistem gerbang otomatis menggunakan YOLOv3 dan RFID, menunjukkan keefektifannya dalam mengatasi tantangan keamanan dan meningkatkan manajemen akses di lingkungan kampus universitas. Penelitian ini menggunakan metode eksperimen untuk mengembangkan sistem pengenalan wajah dan pembacaan kartu di pintu gerbang utama Universitas Mercu Buana. Metode meliputi pengambilan data video menggunakan webcam untuk deteksi objek dengan algoritma YOLOv3, serta penggunaan RFID untuk pembacaan kartu. Data diproses menggunakan Visual Studio Code dan Arduino IDE dengan teknik Grayscale dan median filter untuk pengolahan citra. Evaluasi sistem menggunakan Confusion Matrix menunjukkan keakuratan, presisi, dan recall yang baik. Penelitian ini mengimplementasikan sistem Otomatisasi Pintu Gerbang dengan algoritma YOLOv3 dan RFID di Universitas Mercu Buana. YOLOv3 berhasil mendeteksi wajah secara Real-Time dan RFID memastikan akses hanya untuk yang diotorisasi. Evaluasi dengan Confusion Matrix menunjukkan keakuratan deteksi. Hasilnya menunjukkan peningkatan keamanan dan manajemen akses di kampus. Saran termasuk pengembangan algoritma YOLOv3, eksplorasi teknologi pengolahan citra 3D, dan penelitian lebih lanjut terkait keamanan data dan integrasi dengan teknologi keamanan lainnya. Kata kunci: Pintu Gerbang, ,YOLOv3, RFID, Real-Time Object Detection , Confusion Matrix.
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