Studi Literatur Pemanfaatan Artificial Intelligence untuk Prediksi Bencana Banjir - Zahra, Denada Fatimah; Carkiman, Carkiman (STMIK Subang, 2025)
Floods are disasters that cause losses in the form of material and human casualties if not controlled. The Bekasi flood in 2025 was a flood event that was proven to paralyze economic activities and inundate crucial economic zones and settlements in the Bekasi area. Basically, floods can be categorized as fluvial, pluvial, rob, and flash. There are various factors that cause floods that cause diversity in types and levels of flood destruction. Therefore, previous studies have attempted to predict floods from a physical perspective, but still experience various obstacles, so this study aims to explain the use of artificial intelligence for flood disaster prediction. The research method used is a literature study in order to represent the use of artificial intelligence in various areas and techniques. The data used is in the form of scientific literature consisting of journals and scientific proceedings. The results of the study show that most of the AI used is based on machine learning algorithms, such as random forest, logistic regression, support vector machine, and KNN. Random forest and logistic regression have proven to have the highest performance and accuracy when compared to other algorithms. However, it needs to be combined with data augmentation techniques and consider time when used for real-time prediction needs.