<![CDATA[This study developed a dynamic, web-based integrated spatial disaster profile database system that is highly vulnerable to various types of natural hazards, using Lebak Regency as a case study. The reference for each profile displayed is the Indonesian Disaster Risk (RBI). The output of this study is a web performance overview consisting of an interactive HTML-based frontend integrated with the backend spatial data management using MongoDB, Python, and JavaScript. This system provides district-level statistical summaries, visualizations with thematic classifications, and an automatic update feature via API simulation. In addition, this system integrates spatial and non-spatial data. Based on the evaluation, this system improves the effectiveness of data collection and utilization, supports evidence-based decision making, and strengthens cross-sector collaboration. The use of a non-relational database architecture optimized for dynamic spatial data with synchronous updates and web-based distribution is a major innovation with the hope of creating a standardized and adaptive disaster information system that can be replicated in other regions with similar risks.]]>
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