Prioritization Analysis of Road Improvement Through Traffic Density Data in Central Java Province Using Data Mining Clustering Method Nor Hidayati, Nadia Annisa Maori
Universitas Islam Nahdlatul Ulama Jepara
Abstract
The availability of highway infrastructure will provide optimal service so that the transportation process is faster, safer and more convenient to the destination [1]. Various problems that exist on the road, such as there are potholes that cause water to stagnate when it rains, bumpy roads, cracked roads that cause motorists to be less comfortable when crossing the road, also triggers traffic incidents [2]. A method is needed so that the level of damage can be determined and also the priority of road repairs that will be applied, providing guidelines for investigation/inspection of damage based on traffic density using data mining clustering methods. Traffic density or the amount of average daily traffic (LHR) is very influential on the level of road damage in addition to other factors [3]. The correlation between road improvement and traffic density is very significant so that it can be analyzed using clustering data mining method to facilitate the priority of road improvement in accordance with traffic density. Some of the problems that need to be studied are the characteristics of traffic density in Central Java Province, the development of road repair in Central Java Province, the development of clustering data mining methods in determining road priorities and the development of clustering data mining methods with traffic density in determining road repair priorities in Central Java province. This shows the usefulness of this analysis in education and society. In this analysis determined as many as 3 clusters. Cluster 0 is a road with high traffic density, Cluster 1 is a road with medium traffic density, and Cluster 2 is a road with low traffic density. The density level is also analyzed from the degree of saturation (DS), namely high priority road repair if the value of the degree of saturation (DS) > 1.0- medium priority road repair if the value of the degree of saturation (DS) 1.0>DS>0.75- low priority road repair if the value of the degree of saturation (DS) < 0.75.Keywords: LHR, Density, Clustering data mining
