| Abstrak/Abstract |
In this paper we consider the application of various
machine learning approaches for prediction of the forest fire
occurrence in the peatlands area. Here we consider some
classical classification methods, such as support vector
machine (SVM), k-Nearest Neighborhood (kNN), Logistic
Regression (logreg), Decision Tree (DT) and Naïve Bayes (NB).
For comparison purpose, we also consider more advanced
algorithms, namely AdaBoost (DT based) approach. It is
known that only a little number of similar studies is available
for modeling peatlands fire occurrences in Indonesia. To
illustrate the method, we consider the method using
topographical and meteorological data from South Kalimantan
Province. All computations are done using open source
software R |
