Implementation of K-Means and Hierarchical Clustering in Determining Levels of Smart City 2022 Based on Motion Index

Abstract

Smart City is a city with an innovative development concept. However, not all Smart Cities in countries have the same standard because they are quite heterogeneous. Thus, a cluster analysis was carried out to classify Smart City. The result shows that Smart City is divided into two levels, those are high and low. k-means and hierarchical clustering is used for the method of this research. The grouping is based on the motion index, which consists of economic, environmental, mobilization and transportation indicators, and also international profiles represented by various variables. This research expects that Smart City at a certain level can be compared with other levels, in order to there are improvements and mutual learning about Smart City at a high level. This can also encourage other cities in the process towards Smart City.