Perancangan Aplikasi Prediksi Hotspot Berbasis Data Satelit FIRMS di NTB menggunakan Algoritma Random Forest
DOI:
https://doi.org/10.54706/senastindo.v7.2025.421Keywords:
Hotspot, FIRMS, Random Forest, Prediction, NTBAbstract
Forest and land fires represent a complex environmental issue that requires a predictive approach based on spatial data to support effective mitigation efforts. This study aims to design and implement a hotspot prediction application using satellite data from the Fire Information for Resource Management System (FIRMS) in West Nusa Tenggara Province (NTB), employing the Random Forest algorithm. The dataset was obtained through a web scraping process of NASA FIRMS satellite imagery and processed through stages of data preprocessing, feature engineering, and target variable construction representing the spatial and temporal dimensions of hotspot occurrences. The Random Forest algorithm was selected due to its capability to handle large and complex datasets with high stability and accuracy. Evaluation results indicate excellent classification performance, achieving an accuracy of 98.92%, precision of 99.42%, recall of 99.47%, and an F1-score of 99.45%. The trained model was implemented in a web-based application developed using the Waterfall methodology, featuring interactive prediction and regional filtering by district and sub-district.
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Copyright (c) 2025 Nur Aulia Putri, Annisa Hardianti Faradela, Hamida, Naura Mufliha Marhabani, Arif Rahman
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