Clustering countries according to the logistics  performance index

M Mujiya Ulkhaq

doi:10.35957/jatisi.v10i1.4755

M Mujiya Ulkhaq Diponegoro University

DOI: https://doi.org/10.35957/jatisi.v10i1.4755

Keywords: clustering, clustering algorithm, cluster validation, logistics performance index

Abstract

This study aims to cluster countries according to the logistics performance index (LPI) 2018 data. LPI is one of the indicators for measuring logistics sector performance based on a survey developed by the World Bank since 2007 and has been widely accepted throughout the world. There are 160 countries involved in organizing the 2018 edition of the LPI. It helps countries to understand their current position and develop strategies and policies to improve their performance in world trade. Three clustering algorithms (i.e., k-means, k-medoids, and clustering large applications) are used. To obtain the optimal number of clusters, the elbow method is used. According to the elbow method, the optimal cluster is three for those three clustering algorithms. The countries belong to the first cluster are considered the best performers, while countries in the third cluster are the worst performance in terms of logistics performance. This study is expected to give an insight into how to implement clustering algorithms into the real-world data set and how to interpret the results

Author Biography

M Mujiya Ulkhaq, Diponegoro University

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