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Author

Rojali

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Review Open access Jul 2026

Hybrid Fraud Detection for Government Financial Transactions Using Deep Isolation Forest and Extreme Gradient Boosting: A Case Study from an Indonesian Government Institution

This study proposes a two-stage computational fraud detection framework that integrates Deep Isolation Forest for anomaly detection and Extreme Gradient Boosting (XGBoost) for fraud classification, with an intermediate expert validation process to provide a practical, auditor-aligned approach to public-sector financial...

Ni Komang Yossy Trisna Sukawati Sukawati, Rojali · 1 citation
Conference Jul 2026

Balancing Accuracy and Efficiency in IoT Intrusion Detection Using a Confidence-Based Hybrid LightGBM–CNN Model

Resource-constrained Internet of Things (IoT) environments require intrusion detection systems (IDS) that provide high detection performance while maintaining low computational overhead. Although deep learning models have demonstrated strong predictive capability, their computational complexity often limits deployment...

Darius Felix Lummawie, Rojali, M. E. Syahputra · 0 citations

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