Study of Land Cover Change using Multi Layer Perceptron and Logistic Regression Methods in Gunung Ciremai National Park
Abstract
The development of land cover change is important to understand, so that the pattern of future land cover changes can be predicted and its negative impacts can be prevented or reduced. Various modeling approaches have been widely used to analyze land cover changes. The common modeling methods used for analyzing land cover changes are Multi-layer Perceptron (MLP) and Logistic Regression (Logit). This research is designed to assess the accuracy of modeling of land cover change with MLP and Logit methods in Gunung Ciremai National Park. The result indicated that the accuracy of both methods was very good with kappa values were 0,8991 and 0,8989 for MLP and Logit respectively. Therefore, the model can be applied to predict land cover change in Gunung Ciremai National Park in the future.
Keywords: Gunung Ciremai National Park, land cover change, Logistic Regression, Multi-layer Perceptron
Authors
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