PEMETAAN LOKASI KEBAKARAN HUTAN DAN LAHAN DI NTB DENGAN MENGGUNAKAN ALGORITMA NAIVE BAYES - Rachmawati Oktaria Mardiyanto; Fitriani Fitriani; Ridwan Joko Purnomo; Kusrini Kusrini; Dina Maulina (Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani, 2021)
Forest and land fires are one of the environmental problems in terms of economic and ecological harm. The number of cases of forest fires in the province of NTB has increased dramatically, causing dangerous smog. The increasing incidence of forest and land fires is evidenced by the increasing area burned and the frequency of fires in the last few decades. This study aims to classify the locations of forest and land fires and the causes of fires that occur in NTB. This research has used 104 data in three years (2017-2019) taken from the website of the Department of Environment and Forestry of the province of NTB. The classification model for mapping forest and land fires and the causes of fires uses the Naïve Bayes algorithm with an accuracy value of 55.555%. Thus, it can be concluded that the classification model using Naïve Bayes has the potential to be used effectively so that it can classify the location of forest and land fires and the causes of fires.