Analysis of The Countries According to The Prosperity Level with Data Mining

Abstract

Data mining (DM) includes techniques for finding meaningful information hidden in these massive data stacks. The aim of this study is to divide the countries into groups according to their prosperity levels with Cluster Analysis (CA), which is one of the DM techniques, and to show the applicability of the method. In this context, the 2019 data of 167 countries within the 12 prosperity indicators in The Legatum Prosperity Index (LPI) were used. In the study, countries were divided into groups with the Ward’s algorithm and the similarities between the countries were determined with the K-Means and Turkey's place in the groups was determined. The results show that countries are divided into three clusters according to their prosperity levels. The most effective indicators in dividing them into clusters are "market access and infrastructure, education, investment environment", and the least effective indicators are "social capital, natural environment, safety and security". It has been determined that Turkey is located in the middle prosperity level cluster and its "health, living conditions, education" indicators are the highest, while its "natural environment, personal freedom, management" indicators are the lowest.

Keywords

• Data Mining
• Prosperity Level
• Legatum Prosperity Index
• Cluster Analysis.

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