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Title	Analyze And Predict Car Accidents Using Different Machine Learning Algorithms
ID_Doc	9472
Authors	Harimanto F.P.; Andrew C.; William H.; Asy'ari M.Z.; Artanto S.A.; Puji M.N.
Year	2023
Published	Proceedings of 2023 International Conference on Information Management and Technology, ICIMTech 2023
DOI	http://dx.doi.org/10.1109/ICIMTech59029.2023.10277961
Abstract	Traffic accidents can occur from various factors, ranging from the driver themselves to problems with the vehicle. Road and traffic accidents are the most significant factor of fatalities in the world. Most of the causes of accidents are the drivers themselves. Poor physical and mental conditions can significantly impact how to drive. The driving experience is also important; the longer the driver has been driving, the more professional he will be, and vice versa. Smart City solutions can predict the severity of accidents and give information to the authorities in order to reduce the number of fatalities. This paper investigates the factors that may lead to an accident on the road. By looking at data collected from traffic-related accidents and then visualizing it to make it easy to analyze; then, from this data, we will predict the causes of traffic accidents so they can be avoided. The best algorithm based on accuracy, MAE and RMSE is Random Forest Classifier with 0.8461, 0.1663 and 0.4376, respectively. © 2023 IEEE.
Author Keywords	machine learning; prediction algorithm; traffic accident

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