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Review of Integrating of the GSTARIMA-X Model, Casetti Approach, and Kriging for Climate Data Prediction |
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PP: 1167-1181 |
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doi:10.18576/amis/190516
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Author(s) |
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Ajeng Berliana Salsabila,
Budi Nurani Ruchjana,
Atje Setiawan Abdullah,
Rahmat Budiarto,
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Abstract |
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| This study discusses a systematic literature review to determine the novelty of the GSTARIMA-X model with the Casetti approach and the Kriging method. Based on previous studies, the exogenous variable parameters of the GSTARIMA-X model do not consider the location factor, causing a lack of location factors in the exogenous variables. In this study to overcome this, the GSTARIMA-X model was integrated with the Casetti approach, considering the latitude and longitude coordinates. This can provide location effects on the exogenous variables of the GSTARIMA-X model. This model is called the GSTARIMA-X-Casetti model. The GSTARIMA-X-Casetti model, predictions can only be made at the sampled locations so that the Kriging method is used for predictions at unsampled locations, so the name of the model is GSTARIMA-X-Casetti-Kriging. The model will be applied to climate data, considering that climate data is included in data that can be observed with location and time. The climate data to be used come from NASA POWER which are big data, so the Data Analytics Lifecycle is used for processing.
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