Deteksi Dini Kebakaran Hutan dan Lahan di Kalimantan Tengah


  • Ariesta Lestari Faculty of IT Monash University
  • Grace Rumantir Faculty of IT Monash University
  • Nigel Tapper School of Geography and Environmental Science, Monash University


Forest Fire, Central Kalimantan, Peatland, Data Mining.


Forest fires have become an increasingly serious environmental problem in Indonesia. These fires can lead to major economic losses, widespread health problems, increased local poverty and biodiversity losses. In Central Kalimantan, Indonesia forest fire is a major problem because 20 per cent of the land and forest in this area is peat. Fires occurred in the degraded peatland is dificult to extinguish and can burn for days or weeks. Despite the fact that natural factors such as topography, climate and ecology have a role in forest ire occurrence, many researchers have found that human activities in the forest, i.e. land clearing, timber exploitation, and hunting, have important causal effects on the occurrences of forest fire

To strengthen the capabilities of ire management in Indonesia, especially in Central Kalimantan, it is suggested that enhancing the implementation of detection systems could help to reduce the impact of ires in Indonesia. A range of methods have been employed in forest fire prediction systems. These include traditional statistical hypothesis testing, linear regression, classiication and regression trees and other methods from data mining. Results from related research undertaken in other parts of the world are not readily generalisable to the unique condition of forest fires in Central Kalimantan.