Perancangan Aplikasi Prediksi Kerusakan UAV Menggunakan Algoritma Isolation Forest Berbasis Data Sensor Penerbangan
DOI:
https://doi.org/10.54706/senastindo.v7.2025.422Keywords:
UAV, Isolation Forest, Anomaly Detection, Sensor Data, Predictive MaintenanceAbstract
Unmanned Aerial Vehicles (UAVs) are widely used in mapping, agriculture, and environmental monitoring. One of the main challenges in UAV operations is detecting component failures early. This study aims to design a UAV damage prediction application based on flight sensor data using the Isolation Forest algorithm. The data include motor temperature, vibration, current, and propeller speed collected from UAV telemetry systems. The research process involves data preprocessing, normalization, algorithm implementation, and evaluation using Principal Component Analysis (PCA). The Isolation Forest algorithm was selected for its efficiency in detecting anomalies without labeled data and handling high-dimensional datasets. The results show that the model can accurately detect potential damage and produce stable outcomes. The application was developed using the Waterfall method and includes an interactive dashboard for early UAV failure alerts. This research contributes to predictive maintenance and improves UAV flight safety.
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Copyright (c) 2025 Syahrul Reza, Fatiya Qurrotu'Aini, Khairil Atha, Ninda Cahya Noprianingrum, Arif Rahman, Muhammad Imam Dinata
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