COMPARISON LINEAR REGRESSION AND RANDOM FOREST MODELS FOR PREDICTION OF UNDERGROUND DROUGHT LEVELS IN FOREST FIRES

COMPARISON LINEAR REGRESSION AND RANDOM FOREST MODELS FOR PREDICTION OF UNDERGROUND DROUGHT LEVELS IN FOREST FIRES

The increase in forest fires poses a significant risk due to its impact on underground dryness, which can cause long-term environmental damage and challenge fire suppression efforts. This research aims to develop a prediction model for underground drought levels in the context of forest fires using...

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Bibliographic Details
Main Authors: Nur Alamsyah, Budiman Budiman, Titan Parama Yoga, R Yadi Rakhman Alamsyah
Format: Article
Language:English
Published: Community Service Research Center (LPPM) STMIK Nusa Mandiri Jakarta 2025-01-01
Series:Techno Nusa Mandiri: Journal of Computing and Information Technology
Subjects:
forest fire
linear regression
machine learning
random forest
underground drought
Online Access:https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/5237
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https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/5237

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