Prediction of Forest Fire Occurrence in Peatlands using Machine Learning Approaches

Rosadi, Dedi and Andriyani, Widyastuti and Arisanty, Deasy and Agustina, Dina (2020) Prediction of Forest Fire Occurrence in Peatlands using Machine Learning Approaches. In: International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2020, Universitas Teknologi Digital Indonesia.

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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 Keywords: early warning system, forest fire occurrence, topographical and meteorological data, peat lands fire, machine learning

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Penulis: Dedi Rosadi, Widyastuti Andriyani, Deasy Arisanty, dan Dina Agustina.
Uncontrolled Keywords:	early warning system, forest fire occurrence, topographical and meteorological data, peat lands fire, machine learning
Subjects:	A Karya Umum (General) > Ilmu Komputer (Computer Science) > Kecerdasan Buatan (Artificial Intelegence)
Depositing User:	Titis Pratiwi
Date Deposited:	03 Apr 2023 06:54
Last Modified:	03 Apr 2023 06:54
URI:	http://eprints.utdi.ac.id/id/eprint/9965

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