Skripsi

PENENTUAN JALUR TERBAIK UNTUK SISTEM TRANSPORTASI PINTAR MENGGUNAKAN METODE HISTOGRAM DI KOTA PALEMBANG

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Cities around the world, including the City of Palembang, are facing increasing challenges in terms of transportation management. Population growth, urbanization and continuous population mobility have led to increased traffic, congestion and challenges in achieving efficient mobility. So a research was carried out using various models and algorithms in the context of object recognition, vehicle counting, traffic density prediction, and finding the best route. First, the development of the YOLOv8 model uses 1000 image data files to recognize five object classes with a training accuracy of 88.4% and testing accuracy of 86.16%. Furthermore, the use of YOLOv8 in calculating vehicles from 72 video files for 4 days showed an average accuracy of 89.57% for motorbikes and 93.50% for cars. The ANN model was then applied to classify road conditions with a reading accuracy of 98.96%. Then it was optimized using Random Search and produced a reading accuracy of 100%, while searching for the best route using the Histogram method from Parameswara to Bom Baru, obtained the best weight values and route names depending on the given road conditions.

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Detail Information

Series Title

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Call Number

T1531982024

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xiii, 142 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.30 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Kecerdasan Buatan
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

KA

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