IMPLEMENTASI METODE WNN IMMEDIATE SCAN UNTUK IDENTIFIKASI MATA DAN HIDUNG PADA WAJAH YANG DINAMIS

ROMADHONA, LONDA ARRAHMANDO and Zarkasi, Ahmad (2025) IMPLEMENTASI METODE WNN IMMEDIATE SCAN UNTUK IDENTIFIKASI MATA DAN HIDUNG PADA WAJAH YANG DINAMIS. Undergraduate thesis, Sriwijaya University.

Preview	Image RAMA_56201_09011282025071_Cover.jpg - Cover Image Available under License Creative Commons Public Domain Dedication. Download (719kB) | Preview
	Text RAMA_56201_09011282025071.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy
	Text RAMA_56201_09011282025071_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) | Request a copy
	Text RAMA_56201_09011282025071_0225087902_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (1MB)
	Text RAMA_56201_09011282025071_0225087902_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (827kB) | Request a copy
	Text RAMA_56201_09011282025071_0225087902_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_56201_09011282025071_0225087902_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_56201_09011282025071_0225087902_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (185kB) | Request a copy
	Text RAMA_56201_09011282025071_0225087902_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (189kB) | Request a copy
	Text RAMA_56201_09011282025071_0225087902_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy

Abstract

This research aims to develop a dynamic facial recognition system focusing on the identification of the eye and nose areas. The system utilizes the Weightless Neural Network (WNN) method with the Immediate Scan technique, enabling fast and accurate recognition despite changes in facial positioning. The detection process is carried out using the Haar Cascade Classifier algorithm, which identifies faces and divides the area into nine different zones to ensure precise identification. The system is implemented on the Raspberry Pi as the preprocessing unit and for controlling sensors and robot actuators, while the Arduino Mega functions as the recognition unit embedded with the WNN method. The test results indicate that the proposed system achieves a maximum accuracy of 98.87% when tested with an internal dataset, while tests under different conditions showed a slight accuracy decrease to 92.37%. The highest similarity percentage for faces of other individuals reached 75.69%, demonstrating that this method is fairly adaptive to facial variations. The average processing time for identification ranges between 11 ms and 17 ms, depending on the amount of data compared during scanning. This research is expected to serve as a foundation for further developments in robotic systems and facial recognition based on embedded systems.

Item Type:	Thesis (Undergraduate)
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. T Technology > T Technology (General) > T59.4 Mechanization T Technology > T Technology (General) > T59.5 Automation
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Londa Arrahmando Romadhona
Date Deposited:	21 May 2025 08:08
Last Modified:	21 May 2025 08:08
URI:	http://repository.unsri.ac.id/id/eprint/173478

Actions (login required)

View Item