<![CDATA[This study aims to analyse the vehicle characteristics and traffic density pattern at Mayjen Yusuf Singedekane road section on Palembang which is under the observation of Unit Pelaksana Penimbangan Kendaraan Bermotor (UPPKB) Kertapati by using clustering and time series analysis to process the data recorded by Weigh-in-Motion (WIM) device. The data used in this study includes the time of record, total vehicle weight, number of axles, and weight per axle. The first analysis is performing clustering of the vehicles by weight and axle charactersitics using k-Means clustering method. Second step of the analysis is by finding the traffic density pattern using time series analysis STL Decomposition method to find a short seasonal cycle. These two analysis are done using Orange data mining tool. The result of this study separates the data into 3 clusters: C1 Light represents vehicles with low weight regardless of axles, C2 Heavy represents vehicles with heavy load and focuses on axle configurations between 2 to 4 axles, C3 Large-Heavy represents vehicles with heavy load and focuses on axle configurations between 5 to 6 axles. This study determines that the weekly density pattern peaks at Friday and reaches the lowest point at Saturday. Hopefully these findings are able to contribute to the planning of traffic management and road infrastructure maintenance efforts among other potential uses.]]>
Copyrights © 2026
