1. The implementation of GSTARI-X model for forecasting climate change with data mining approach.
- Author
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Monika, Putri, Ruchjana, Budi Nurani, and Abdullah, Atje Setiawan
- Abstract
Climate change is one of Indonesia's most widely discussed and studied environmental problems. Based on the purpose of the 13th SDGs goals, climate change urgently requires rapid action to overcome it. It becomes a challenge for researchers to forecast the state of the climate in the future. In this study, one of the climate parameters was forecasted, namely rainfall and humidity, through the Generalized Autoregressive Integrated with Exogenous Variable (GSTARI-X) model. The GSTARI-X model is a model that examines phenomena that are ordered spatially and time is simultaneously or commonly known as the Space-Time model. Applying the GSTARI-X model in forecasting rainfall with humidity as an exogenous variable used the Knowledge Discovery in Database (KDD) data mining approach. The KDD Data Mining method is needed because the climate data is sourced from NASA observation data which is big data. The function of the KDD method in this study is to describe and predict climate phenomena, especially in West Java. This study's expected results forecast future climate phenomena, which are presented through rainfall maps using the QGIS program. The results of climate forecasts using the GSTARI-X model have an accurate forecasting capability with MAPE values of 18% and 15%. This can be a recommendation for related agencies in policy making. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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