Analisa Slope Wilayah Kebakaran Hutan Menggunakan Metode Naïve Bayes

Abstract

Forest and land fires are an economic and environmental problem that can cause serious damage. We can predict what factors cause forest fires. It is undeniable that topographical conditions affect the triggering and propagation of fires. The topographical condition itself is in the form of a slope, where fire propagation will be faster when going up the slope than going down the slope. This study aims to match whether the slope and display locations that are prone to the spread of certain fires with high fire intensity actually have a high fire potential and report the magnitude of the influence of the slope in the prediction of fire potential. One of the common approaches to classifying data is to use data mining. So in this study the researchers used the Naive Bayes Classifier as a classification method by getting the highest accuracy value of 0.99%.