TY - GEN
T1 - Analyzing highway road accident characteristic using data mining
AU - Ilham, Muhammad Yogi
AU - Surjandari, Isti
AU - Laoh, Enrico
N1 - Funding Information:
Authors would like to express gratitude and appreciation to Universitas Indonesia for funding this study through PUTI B Research Grants Universitas Indonesia NKB-0705/UN2.R3.1/HKP.05.00/2019.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/17
Y1 - 2020/10/17
N2 - 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.
AB - 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.
KW - Association Rule Mining
KW - Clustering
KW - Highway
KW - Road Accident
UR - http://www.scopus.com/inward/record.url?scp=85097632374&partnerID=8YFLogxK
U2 - 10.1109/IWBIS50925.2020.9255655
DO - 10.1109/IWBIS50925.2020.9255655
M3 - Conference contribution
AN - SCOPUS:85097632374
T3 - 2020 International Workshop on Big Data and Information Security, IWBIS 2020
SP - 17
EP - 21
BT - 2020 International Workshop on Big Data and Information Security, IWBIS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Workshop on Big Data and Information Security, IWBIS 2020
Y2 - 17 October 2020 through 18 October 2020
ER -