As an archipelagic country, Indonesia faces challenges in developing sustainable coastal areas and communities. Most studies have focused on specific regions, limiting broader generalizations. This study focuses on coastal villages in Indonesian provinces. The objectives are to classify provinces according to the environmental, economic, and social pillars of sustainability; classify provinces based on overall sustainability; and examine the sustainability level of coastal villages using macroeconomic indicators. A data mining approach was applied using the Knime Analytics Platform. The findings revealed that environmental sustainability tends to be less prominent than economic and social aspects. Provincial classifications show varying levels of sustainability across regions. Coastal villages in high-sustainability provinces tend to have higher life expectancy, lower poverty rates, and higher Human Development Index scores than those in low-sustainability provinces. These high-sustainability provinces also demonstrated vigorous blue economy activities, particularly aquaculture and marine tourism. In contrast, low-sustainability provinces lag in these areas. The study suggests prioritizing the development of aquaculture and marine tourism in low-sustainability coastal provinces as a strategic approach to promote inclusive and sustainable blue economy growth. A novel aspect of this research lies in the application of national-scale data mining using k-means clustering to uncover spatial and social, economic, and environmental patterns across regions, demonstrating the potential of large-scale analytics for sustainability understanding in coastal areas.
Gunawan Gunawan (Mon,) studied this question.