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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Intelligent Decision Support System (IDSS) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Journal Of Indonesian Social Society Jurnal ICT : Information and Communication Technologies Journal of Technology and Computer (JOTECHCOM) JIPITI: Jurnal Pengabdian kepada Masyarakat
Dhany, Hanna Willa
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

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Optimizing Urban Traffic Management Through Advanced Machine Learning: A Comprehensive Study Izhari, Fahmi; Dhany, Hanna Willa
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 4 (2023): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i4.167

Abstract

Urban transport networks are vital components of modern societies, influencing efficiency and safety. This research explores the potential of traffic data as a crucial information source for forecasting and interpreting traffic problems. Using advanced data processing, statistical analysis, and classification algorithms, the study aims to identify and forecast traffic scenarios. With an interdisciplinary approach integrating computer science, statistics, and transportation engineering, the research emphasizes a holistic perspective on traffic concerns. The study involves outlier detection, label encoding, and cutting-edge technologies like GridSearchCV and ensemble modeling. Inspired by flash flood susceptibility research, machine learning models, particularly LightGBM and CatBoost, are applied to predict traffic situations. DecisionTreeClassifier and CatBoostClassifier emerge as top performers, achieving remarkable accuracies. The evaluation goes beyond accuracy, emphasizing the nuanced understanding of algorithm strengths and limitations for effective urban transportation network management
Co-Authors Aritonang, Dhimas Ansyahri Enda Ribka Meganta P Izhari, Fahmi Mhd Rifqi Aditya Ricky Ramadhan Harahap Saragih, Muhammad Davy Anggara Sinaga, Santi Anggryani Sutarman Sutarman Wijaya, Rian Farta