Skripsi

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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507002871	T173478	T1734782025	Central Library (REFERENCE)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1734782025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xix, 111 hlm.; ill.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

TUTI

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