Skripsi

KLASIFIKASI GOLONGAN KENDARAAN DI JALAN TOL MENGGUNAKAN METODE DEEP LEARNING BERBASIS CITRA BERGERAK

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Penilaian

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Motorized vehicles operating on toll roads play an important role in the mobility of modern society. Efficient traffic monitoring and management is an important aspect in maintaining the safety and comfort of toll road users. The research proposes the use of the YOLOv7 (You Only Look Once version 7) method to classify vehicle groups operating on toll roads. Moving images were chosen as input to the program developed by the researcher, which will also be the program output format where the program output has been given a bounding box for vehicles that have been successfully detected and classified. The program built uses 3 combinations of Epoch and batch size, namely Batch 16 Epoch 55, Batch 16 Epoch 250, and Batch 16 Epoch 400 to obtain the feature model for the testing process. The results of the testing process obtained Precision values of 0.963, Recall 0.976, and Accuracy 0.953. This system has great potential for the development of technological progress and progress in toll traffic in Indonesia.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307006422	T130902	T1309022023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1309022023

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

ix, 72 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.107

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Informatika
Identifikasi Sistem

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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