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

  • Zahrah S
  • Handayani A
  • Nurdin A
N/ACitations
Citations of this article
27Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Zahrah, S. A., Handayani, A. S., & Nurdin, A. (2022). Implementasi Support Vector Machine Pada Alat Monitoring Kecelakaan Dengan Intelligent Transport System. Building of Informatics, Technology and Science (BITS), 4(2), 562–569. https://doi.org/10.47065/bits.v4i2.1974

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free