K-NN ALGORITHM AS A DECISION SUPPORT TOOL FOR DETERMINING EVACUATION PRIORITIES IN AREAS AFFECTED BY TSUNAMI POTENTIAL

Abstract

Tsunamis are among the many types of natural disasters that can cause severe and often fatal destruction. A tsunami is defined as a large ocean wave generated by geological activities such as earthquakes, volcanic eruptions, or the shifting of underwater tectonic plates. Due to their high speed and immense power, tsunamis can result in massive flooding and extensive damage to coastal areas.

The objective of this study is to assess the tsunami potential of each earthquake event. Furthermore, for those earthquakes identified as having tsunami potential, the study aims to determine which areas should be prioritized for evacuation efforts.

This research employs several methods, including literature review, field study, data collection, data analysis, system development, and method validation. The decision-making criteria used in this study include tsunami potential, distance from the sea, distance to high ground, and the number of households. The dataset consists of 30 records, of which 70% are designated for training, while the remaining 30% are set aside for testing purposes. The algorithms applied are K-Nearest Neighbors (K-NN) for classification and the Weighted Product method for decision-making.