Urban vulnerability to floods investigation in jakarta, Indonesia: A hybrid optimized fuzzy spatial clustering and news media analysis approach

Abstract

Jakarta, known as the capital city of Indonesia and the national economic activity center, is also known as the market for floods. Moreover, the regions of Jakarta become vulnerable, especially the slum areas and this COVID-19 pandemic. This study proposes implementing Fuzzy Geographically Weighted Clustering (FGWC) with Chaotic Flower Pollination Algorithm (CFPA) in urban vulnerability analysis of Jakarta at the subdistrict level. Moreover, this study also implements the named entity recognition (NER) from local news media to extract the history of floods in Jakarta during 2019–2020 to support the urban vulnerability. This study found that the CFPA can improve the performance of FGWC. Subsequently, the clustering results showed that each cluster has its urban vulnerability problem. Most regions outside central Jakarta have more vulnerability problems, particularly in population dynamics, floods history, and slum areas. On the other hand, the news analysis showed that the most frequent flood happened between October and February. Therefore, the government and society must collaborates to overcome the urban vulnerability problems and mitigates the floods to increase the regional resilience of Jakarta.