Mapping of Social Vulnerability to Natural Hazards in Geodemographic Analysis Using Fuzzy Geographically Weighted Clustering

Assessing social vulnerability is essential for addressing environmental risks by developing suitable adaptation strategies and fostering a resilience mindset. However, relying solely on an index-based approach to measure social vulnerability has limitations as it only provides a broad overview. It is essential to recognize that various regions are influenced by distinct factors contributing to social vulnerability. This study aims to pinpoint specific community factors that impact vulnerability to natural disasters in various districts across Indonesia. In this research, we determine the optimal number of clusters with the Cluster Validity Index (CVI). Furthermore, this research applies clustering analysis of social vulnerability to natural disasters at the district level using the Fuzzy Geographically Weighted Clustering (FGWC) algorithm. This research highlights varying social vulnerability profiles across Indonesia’s diverse districts. Specifically, districts on the western side of Sumatra Island, such as Nias and Mentawai, and those in the eastern regions of Indonesia, including Nusa Tenggara, West Sulawesi, Central Sulawesi, North Sulawesi, the Southern Maluku Islands, and Papua, exhibit the most noticeable vulnerability. This vulnerability is particularly evident in socioeconomic indicators, family composition, housing conditions, and educational access.

Scientific Journal of Informatics Vol.10 No.4 2023