Forest Fire Prediction in Northern Sumatera using Support Vector Machine Based on the Fire Weather Index

Darwis Robinson Manalu1, 2, Muhammad Zarlis1, Herman Mawengkang1 and Opim Salim Sitompul1, 1Universitas Sumatera Utara, Indonesia, 2Universitas Methodist Indonesia, Indonesia; Darwis Robinson Manalu1, 2, Muhammad Zarlis1, Herman Mawengkang1 and Opim Salim Sitompul1, 1Universitas Sumatera Utara, Indonesia, 2Universitas Methodist Indonesia, Indonesia

Forest Fire Prediction in Northern Sumatera using Support Vector Machine Based on the Fire Weather Index

Authors

Darwis Robinson Manalu^{1, 2}, Muhammad Zarlis¹, Herman Mawengkang¹ and Opim Salim Sitompul¹, ¹Universitas Sumatera Utara, Indonesia, ²Universitas Methodist Indonesia, Indonesia

Abstract

Forest fires are a major environmental issue, creating economical and ecological damage while dangering human lives. The investigation and survey for forest fire had been done in Aek Godang, Northern Sumatera, Indonesia. There is 26 hotspot in 2017 close to Aek Godang, North Sumatera, Indonesia. In this study, we use a data mining approach to train and test the data of forest fire and the Fire Weather Index (FWI) from meteorological data. The aim of this study to predict the burned area and identify the forest fire in Aek Godang areas, North Sumatera. The result of this study indicated that Fire fighting and prevention activity may be one reason for the observed lack of correlation. The fact that this dataset exists indicates that there is already some effort going into fire prevention.

Keywords

Forest fire, Fire Weather Index, Support Vector Machine, Machine Learning

CS&IT Conference Proceedings

Forest Fire Prediction in Northern Sumatera using Support Vector Machine Based on the Fire Weather Index