IMPLEMENTASI FACE RECOGNITION PADA SISTEM KEAMANAN SEPEDA MOTOR

ADRIAN, AFRILA (2024) IMPLEMENTASI FACE RECOGNITION PADA SISTEM KEAMANAN SEPEDA MOTOR. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The implementation of facial recognition in a motorbike security system is a facial authentication system that is implemented on motorbikes to anticipate criminal acts such as motorbike theft. The facial authentication system uses a Huskylens AI sensor component which is equipped with a facial recognition feature that can be used for facial authentication. To use the face recognition feature, the device needs to do face learning on the user's face first. The system uses an Arduino Uno board as a controller for facial data detected by the Huskylens. If the detected face is a face that has been registered and face learning has been carried out previously, the Arduino will activate the relay as a connector or breaker for the motorbike's electrical system. Trials were carried out to see the system response if Huskylens detected a registered user or an unregistered user and to compare the use of accessories on the face with those who did not wear accessories. The system performance results show that the system can detect registered users' faces with an accuracy of 71.42%. Face detection accuracy when using facial accessories is 12.5%. The response time of the Huskylens to recognize faces is less than 4 seconds with data reading accuracy of 100%. Meanwhile, the time required to start the motorbike if facial authentication is successful is less than 16 seconds. How long the system's facial recognition process takes is influenced by light factors, the distance between the face and the camera, and the accessories used by the user. Keywords: Motorcycle, Huskylens, Face Recognition, Face Learning Implementasi face recognition pada system keamanan sepeda motor merupakan sebuah system autentikasi wajah yang diimplementasikan pada sepeda motor untuk mengantisipasi terjadinya tindak criminal akan pencurian sepeda motor. Sistem autentikasi wajah menggunakan komponen sensor AI huskylens yang dilengkapi dengan fitur face recognition yang dapat digunakan untuk autentikasi wajah. Untuk menggunakan fitur face recognition, perangkat perlu dilakukan face learning terhadap wajah user terlebih dahulu. Sistem menggunakan board Arduino uno sebagai pengontrol data wajah yang dideteksi oleh huskylens. Jika wajah terdeteksi adalah wajah yang sudah terdaftar dan dilakukan face learning sebelumnya maka Arduino akan mengaktifkan relay sebagai penghubung atau pemutus system kelistrikan pada sepeda motor. Uji coba dilakukan untuk melihat respon sistem jika huskylens mendeteksi user terdaftar ataupun user yang tidak terdaftar serta membandingkan pemakaian aksesoris pada wajah dengan yang tidak memakai aksesoris. Hasil performansi sistem menunjukkan bahwa sistem dapat mendeteksi wajah user terdaftar dengan akurasi 71.42 %. Akurasi pendeteksian wajah saat menggunakan aksesoris wajah adalah 12.5%. Respon time huskylens mengenali wajah kurang dari 4 detik dengan akurasi kesesuaian pembacaan data adalah 100%. sementara itu waktu yang diperlukan untuk menyalakan sepeda motor jika autentikasi wajah berhasil adalah kurang dari 16 detik. Lama tidaknya proses pengenalan wajah oleh sistem dipengaruhi oleh faktor cahaya, jarak wajah dengan kamera, dan aksesoris yang dipakai oleh user. Kata kunci : Sepeda Motor, Huskylens, Face Recognition, Face Learning.

Item Type:	Thesis (S1)
Call Number CD:	FT/ELK. 24 001
Call Number:	ST/14/24/001
NIM/NIDN Creators:	41422110083
Uncontrolled Keywords:	Sepeda Motor, Huskylens, Face Recognition, Face Learning
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan > 006.31 Machine Learning/Pembelajaran Mesin 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.4 Computer Pattern Recognition/Pola Pengenalan Komputer > 006.45 Acoustical Pattern Recognition/Pengenalan Pola Akustik > 006.454 Speech Recognition/Pengenalan Suara 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 629 Other Branches of Engineering/Cabang Teknik Lainnya > 629.2 Motor Land Vehicles and Cycles Engineering/Teknik Kendaraan Bermotor dan Teknik Sepeda 700 Arts/Seni, Seni Rupa, Kesenian > 700. Arts/Seni, Seni Rupa, Kesenian > 702 Miscellany of Fine and Decorative Art/Aneka Ragam tentang Kesenian, Aneka Ragam tentang Karya Seni > 702.8 Techniques, Precedures, Apparatus, Equipment, Materials/Teknik, Prosedur, Perlengkapan, Peralatan, Bahan > 702.89 Safety Measures/Keamanan
Divisions:	Fakultas Teknik > Teknik Elektro
Depositing User:	khalimah
Date Deposited:	06 Feb 2024 04:12
Last Modified:	06 Feb 2024 04:12
URI:	http://repository.mercubuana.ac.id/id/eprint/85872

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