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Abstract ABS-21

Multivariate Time-Series Flood Prediction Using LSTM Networks and GIS-Based Visualization of Meteorological Data from BMKG Rando (a*), Agusman (a) Corresponding Author: Rando Rando

Question from Dr. Safrin Salam 2025.12.16 09:06:39 How does the integration of multivariate time-series data in LSTM networks improve flood prediction accuracy, and in what ways does GIS-based visualization of BMKG meteorological data enhance decision-making for early flood warning and disaster mitigation?

Reply from Mr. Rando Rando 2025.12.16 10:23:28 GIS-based visualization enhances early flood warning and disaster mitigation by transforming BMKG meteorological data and model predictions into spatially explicit and easily interpretable maps. By integrating forecasting results within a geographic context, decision-makers can rapidly identify high-risk locations, assess spatial variability, and prioritize response actions. This spatial perspective improves situational awareness, supports more targeted mitigation strategies, and strengthens communication between technical analysts and local disaster management authorities.

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