MODELING THE IMPACT OF SEA-LEVEL RISE ON COASTAL VULNERABILITY IN JAKARTA USING AN INTEGRATED DATA SCIENCE FRAMEWORK - Nofirman Nofirman; Dulguun Amarsaikhan; Munkhzul Ganbat; Tugsuu Jargalsaikhan (Scientechno: Journal of Science and Technology, 2025)
Jakarta, the capital city of Indonesia, is highly vulnerable to the impacts of sea-level rise due to its coastal location, rapid urbanization, and subsidence, making it crucial to understand how climate change-driven increases in sea levels affect the city’s coastal areas for effective adaptation planning. This study aims to model the impact of sea-level rise on the vulnerability of Jakarta’s coastal zones by using an integrated data science framework to assess potential risks such as flooding, land loss, and other environmental consequences under various sea-level rise scenarios. Employing a combination of geographic information systems (GIS), remote sensing data, and machine learning models, the analysis integrates sea-level rise projections with land elevation, population density, and infrastructure data to evaluate potential impacts, while algorithms such as Random Forest and Support Vector Machine (SVM) are utilized to predict vulnerability levels. The results indicate that Jakarta’s coastal areas face high vulnerability, with substantial portions of land projected to be inundated under higher sea-level scenarios, particularly in low-lying and densely populated regions at heightened risk of flooding and infrastructure damage. Overall, this research offers valuable insights into future coastal vulnerability in Jakarta and demonstrates how an integrated data science approach can support urban planning and climate adaptation strategies aimed at reducing the risks associated with rising sea levels.