Prediction of forest fire occurrences in peatlands - Unbalanced - Data using hybrid ADASYN-machine learning method

Rosadi, Dedi and Arisanty, Deasy and Andriyani, Widyastuti (2024) Prediction of forest fire occurrences in peatlands - Unbalanced - Data using hybrid ADASYN-machine learning method. In: 6th International Conference on Mathematics and Mathematics Education, ICM2E 2022, 3 September 2022 through 4 September 2022, Padang.

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Abstract

The literature review found that only a few studies in Indonesia have been applied to modeling peatlands fire occurrences. In our previous studies, various machine learning classification approaches are applied to predict forest fire occurrence in the peatlands area. Our previous empirical study found that the datasets of fire hotspot areas, especially for data from the South Kalimantan area, need to be more balanced. In this paper, we consider ADAptive SYNthetic (ADASYN) method for the sampling approach to balance the datasets. We found that by balancing the data, the performance of the classification method can improve about 2-4%.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Mathematics and Natural Sciences > Mathematics Department
Depositing User: Ismu WIDARTO
Date Deposited: 03 Jul 2025 08:50
Last Modified: 03 Jul 2025 08:50
URI: https://ir.lib.ugm.ac.id/id/eprint/19380

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