Dicky Aulia Septian, Lastri Ramadani Siburian, Rafi Ariq Hakim, Fitri Kartiasih

The Effect of Green Economy Indicators on Human Quality of Life in Indonesia in 2021

Introduction

The effect of green economy indicators on human quality of life in indonesia in 2021. Explore how green economy indicators impact Indonesia's human quality of life (HDI) in 2021. Forest cover & poverty reduce HDI; GRDP significantly increases it.

Abstract

Economic development has serious implications for environmental sustainability, affecting the well-being of people in a country. This problem requires initiatives to implement green economy policies with the principle of involving economic development in line with the efficient use of natural resources so as to achieve a good quality of human life. This study aims to analyze the effect of green economy implementation on the quality of human life with descriptive and inferential analysis methods. This research uses multiple linear regression analysis and K-Means Clustering. With the K-Means Clustering method, three provincial clusters with the lowest to highest average Human Development Index (HDI) were obtained. The results showed that the area of forest land cover and poverty line significantly reduced HDI. However, Gross Regional Domestic Product per Capita at Current Prices significantly increases HDI. This study highlights the crucial role of green economy in shaping development pathways that are not only focused on economic growth, but also on maintaining ecological balance and improving human quality of life.

Review

This study addresses a highly pertinent topic, investigating the impact of green economy indicators on the quality of human life in Indonesia, specifically for the year 2021. The central premise that economic development must align with environmental sustainability to foster human well-being is timely and crucial, reflecting global priorities for sustainable development. The stated aim to analyze this effect through descriptive and inferential methods, incorporating both multiple linear regression and K-Means Clustering, suggests a robust analytical approach to a complex issue, promising valuable insights into the interdependencies between economic, environmental, and social dimensions. The methodological choice to employ K-Means Clustering to group provinces based on their Human Development Index (HDI) prior to regression analysis is a notable strength, potentially allowing for a more nuanced understanding of how green economy factors manifest across different levels of development within Indonesia. The empirical findings are significant: the study reveals that the area of forest land cover and the poverty line significantly *reduce* HDI, underscoring critical environmental degradation and socio-economic challenges. Conversely, Gross Regional Domestic Product per Capita at Current Prices significantly *increases* HDI, reinforcing the traditional link between economic output and human development. These results provide empirical backing for the intricate relationships between ecological health, economic prosperity, and the quality of life. While the study's findings are valuable, the abstract could benefit from greater clarity regarding the specific "green economy indicators" utilized in the regression analysis. The title broadly refers to "Green Economy Indicators," but the results primarily highlight forest land cover (a clear environmental indicator), poverty line (a socio-economic indicator), and GRDP (a traditional economic indicator). A more explicit articulation of how poverty line and GRDP are conceptualized within the *green economy* framework, or if they serve as control/moderating variables, would strengthen the theoretical coherence. Furthermore, given the "crucial role" highlighted, a brief discussion of potential policy implications stemming directly from these findings would enhance the study's practical impact and guide policymakers in Indonesia towards more sustainable and equitable development pathways.

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