Klasifikasi Titik Api di Bengkalis Riau Menggunakan Algoritme ID3 Spasial yang Diperluas

Abstract

Forest fire in Riau Province including Bengkalis district, are frequently occurred every year. Hotspot is an indicator for forest fire events. Hotspots monitoring by the NOAA satellite is one of the efforts to prevent forest fires. Hotspot data are spatial data. In order to analyze the data, spatial algorithms are required. The extended spatial ID3 algorithm is a spatial classification algorithm for creating a spatial decision tree from spatial datasets. This research applied the extended spatial ID3 algorithm to the forest fires data in Bengkalis district, Riau. The data include hotspots and non-hotspots, weather data, socio-economic data, and geographical characteristics of the study area. The result of this research is a decision tree with income source layer as the root node. As many as 137 rules were generated to the tree. The accuracy of the tree is 75.66% and 41.38% respectively on the forest fires dataset in Bengkalis district and Rokan Hilir district Riau.