Drivers and Cluster Analysis of Happiness in Indonesia BPS, IPB University
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Cluster analysis, happiness, subjective well-being
Abstract
Welfare is one of the goals of state development. Measuring the success of a country's development often uses monetary measures, such as gross domestic product (GDP). However, GDP tends to ignore aspects that contribute to a person's quality of life and happiness. This thesis focuses on examining the factors driving happiness in Indonesia and categorizing the provinces into categories that have similar characteristics so that policies can be more targeted and efficient. The Indonesian happiness index resulting from the 2021 happiness survey was analyzed using the multiple linear regression statistical method. The results show that the Gini coefficient has a negative effect on happiness, and GDP per capita has a positive effect. This thesis further categorizes 34 provinces in Indonesia into 3 categories of high, low, and medium levels of the value of each indicator. From these results, the government can focus policies related to inequality between regions and GDP per capita, based on the characteristics of each cluster.
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