Implementasi Support Vector Machine Pada Alat Monitoring Kecelakaan Dengan Intelligent Transport System

Syifa Amira Zahrah (Politeknik Negeri Sriwijaya, Palembang)
Ade Silvia Handayani (Politeknik Negeri Sriwijaya, Palembang)
Ali Nurdin (Politeknik Negeri Sriwijaya, Palembang)

Building of Informatics, Technology and Science
Vol 4 No 2 (2022): September 2022

The implementation of intelligent transportation systems will produce a large amount of data. The resulting data is critical in the design and implementation of ITS in the transportation system. This study discusses the performance of the Support Vector Machine algorithm on an accident monitoring tool by utilizing the Intelligent Transportation System that works in real-time using an Android-based application. This experiment simulates accident monitoring with a multisensor accident monitoring device. Multisensor technology consists of MPU 6050 sensor, sound sensor, vibration sensor, and camera. In an experiment, the measured variables are location, slope, accuracy, and time of the traffic accident monitoring system. The results of monitoring traffic accidents in testing using the Support Vector Machine algorithm can work well by classifying data based on the type of accident.