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R. Arista

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Open access Sep 2026

Comparative Analysis of Random Forest, BiLSTM, and Isolation Forest for Rainfall Data Anomaly Detection to Support Automatic Rain Gauge (ARG) Performance Monitoring

This study aims to evaluate and compare the performance of the Random Forest, Bidirectional Long Short-Term Memory (BiLSTM), and Isolation Forest algorithms in detecting anomalies in rainfall data, as well as to implement these methods in a web-based monitoring system.

R. Arista, Adi Widiatmoko Wastumirad, Marzuki Sinambela et al. · 0 citations

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