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Aryatama, Andrew Ananta
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Implementasi Artificial Neural Network dalam Identifikasi Fatalitas Kecelakaan Lalu Lintas (Studi Kasus: Kota Leeds-Inggris) Aryatama, Andrew Ananta; Wowor, Alz Danny
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i4.1102

Abstract

Traffic accidents are a serious worldwide problem, including in Leeds, England. The high fatality rate of traffic accidents is a significant challenge in improving road safety. Therefore, this research aims to implement artificial neural networks in analyzing the factors contributing to traffic accident fatalities in Leeds. The method used in this research involves collecting data of traffic accidents from 2009 to 2018 in the town of Leeds. This method was chosen because artificial neural networks can perform complex and in-depth analyses of large and complex data. This research concludes that artificial neural networks can be used as an effective tool in analyzing traffic accident data and helping policymakers improve road safety in Leeds and possibly elsewhere.
Co-Authors Alz Danny Wowor