Unravelling Income Inequality in Indonesia
A Machine Learning Approach to Understanding The Impact Of Information and Communication Technology
DOI:
https://doi.org/10.23969/jrie.v3i2.63Keywords:
Information and Communication Technology, Income Gap, Machine Learning, Linear Regression, K-means ClusteringAbstract
This study aims to analyze the effect of Information and Communication Technology (ICT) on income inequality in Indonesia. The analytical method used includes linear regression to evaluate the causal relationship between the dependent variable (Gini Ratio) and ICT indicators. Furthermore, the k-means clustering algorithm is used to group provinces based on ICT characteristics. The results of the regression analysis show that the ICT variables have a significant influence on the Gini Ratio, illustrating the close relationship between ICT and income inequality. In addition, clustering produces two regional groups: Cluster 1, with better access and use of ICT, and Cluster 2, with lower ICT characteristics but advantages in telecommunication infrastructure. This research shows the importance of inclusive and sustainable ICT development to reduce income inequality in Indonesia. Appropriate policies for increasing the accessibility and use of ICTs can have a positive impact on social and economic development throughout Indonesia.
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