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All Journal EPI International Journal of Engineering
Indah Yessi Kairupan
Department of Information Systems, Institut Agama Kristen Negeri Manado, Indonesia.
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Predicting Flood Risk in Manado City Using the C4.5 Decision Tree Algorithm: A Data-Driven Approach Apriandy Angdresey; Indah Yessi Kairupan; Ranodeyansa Rumanjar; Andre Gabriel Mongkareng; Ignatius Lucky Henokh Tangka
EPI International Journal of Engineering Vol 8 No 2 (2025): Volume 8 Number 2, August 2025
Publisher : Center of Techonolgy (COT), Engineering Faculty, Hasanuddin University

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Abstract

Flooding, a natural disaster commonly triggered by heavy rainfall or blocked waterways, poses a persistent threat to Manado City due to its proximity to the sea and major rivers, Tondano and Tikala. This study develops a flood prediction application using the C4.5 Decision Tree algorithm based on historical data (2017–2021) from five rivers. Input variables include rainfall, water discharge, runoff coefficients, and river cross-sectional data. The model supports the Sulawesi River Regional Office I by predicting flood conditions—flood, prone to flooding, or no flooding—to enhance mitigation strategies. Experimental results show robust predictive performance, achieving accuracies of 86.13%-87.07% across different data splits. Future integration with the Internet of Things (IoT) is proposed to enable real-time data acquisition, thereby improving the system's responsiveness and flood risk management effectiveness.
Co-Authors Andre Gabriel Mongkareng Apriandy Angdresey Ignatius Lucky Henokh Tangka Ranodeyansa Rumanjar