Analyzing highway road accident characteristic using data mining

Muhammad Yogi Ilham, Isti Surjandari, Enrico Laoh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Road accident is an undesirable event that causes injuries and material damage. Recently in Indonesia, the increasing trend of road accidents has caused significant damage in fatalities and infrastructure. In order to reduce the number of road accidents, necessary information is required so decision-makers could take action. Data mining offers technique to analyze extensive data which is advantageous due to road accident heterogeneous nature. The clustering method is used to group data in order to reduce heterogeneity, and association rule mining method is used to find common characteristics of each clusters. There are thirteen clusters found. Each clusters are analyzed further using association method. The data used in this research is Highway accident in Cikopo-Palimanan Toll road 2017-2019.

Original languageEnglish
Title of host publication2020 International Workshop on Big Data and Information Security, IWBIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages17-21
Number of pages5
ISBN (Electronic)9781728190983
DOIs
Publication statusPublished - 17 Oct 2020
Event5th International Workshop on Big Data and Information Security, IWBIS 2020 - Depok, Indonesia
Duration: 17 Oct 202018 Oct 2020

Publication series

Name2020 International Workshop on Big Data and Information Security, IWBIS 2020

Conference

Conference5th International Workshop on Big Data and Information Security, IWBIS 2020
Country/TerritoryIndonesia
CityDepok
Period17/10/2018/10/20

Keywords

  • Association Rule Mining
  • Clustering
  • Highway
  • Road Accident

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