Skripsi

PROTOTIPE SISTEM KEAMANAN AKSES MASUK RUANGAN BERBASIS FINGERPRINT RECOGNITION MENGGUNAKAN ALGORITMA DEEP LEARNING

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Penilaian

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The password is the oldest security system that is still used today. However, the security system is vulnerable to cyber attacks, especially brute force. The biometric security system is one of the solutions to improve the current security system. Fingerprints are one of the most frequently used biometrics today. In this study, the fingerprint recognition system is implemented in the form of a prototype with recognition using deep learning architecture from convolutional neural network (CNN). The training results show that ResNet50 does not experience significant overfitting compared to the other two architectures with loss value 0,9935% and accuracy 100%. Offline testing uses test data on ResNet50 with variable "open for the right person" getting a value of 95.58% while EfficientNetV2M and VGG16 get a value of 93.13% and 86.76%. So that the prototype used ResNet50 as a fingerprint recognition system. However, online testing on ResNet50 still not able to generalize new data especially in the condition of damaged fingerprints.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307005495	T119492	T1194922023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1194922023

Publisher

Indralaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya., 2023

Collation

xvi, 59 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

621.390 7

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)

Teknik komputer
Prodi Teknik Elektro
Sistem Absensi

Specific Detail Info

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Statement of Responsibility

PITRIA

Other version/related

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