Analysis of Freight Mode Characteristics on The Northern Coastline Route using Mixed Data Based Cluster Analysis

Abstract

Due to the increase in the number of vehicles, the maintenance cost on north coast roads (Pantura route) increases because many of its parts are damaged, potholed, and other problems. Mode switching is expected to produce more efficiently, and grouping a mode's characteristics are proven to classify which products need to undergo a modal shift.  In this study, a grouping of goods truck modes will be carried out based on the characteristics of the trip, the traveler, and the transportation system on the Northern coastline route to then provide policy recommendations for switching to another mode on the goods truck mode at the Northern coastline route with mostly possible characteristics. The method used for the grouping in this research is clustering analysis, particularly the k-prototype clustering method, and partitions around medoids because the data contains mixed variables, i.e., both categorical and numerical variables.

Keywords: Cluster Analysis; Freight Transport; Mixed Data; Transportation