Prediction of Tidal Data Using Cloud Computing-Based Support Vector Regression in Alor, East Nusa Tenggara
DOI:
https://doi.org/10.35335/mandiri.v11i1.128Keywords:
Alor, Pasang surut, Support Vector Regression, Cloud ComputingAbstract
Alor Regency is an area located at 8o6' South Latitude – 8o36' South Latitude and 123o48' East Longitude – 25o 48' East Longitude. Alor as an archipelagic region with wide waters and rich in various types of fishright. The tides (tidal) of sea water is a phenomenon of periodic ups and downs of sea levels that can affect the activities of coastal communities. The existence of today's technological advances by predicting the height of the tides can be a control for the sustainability of community activities in coastal areas affected by the tides. Predictions are made using tidal data in time series since 2019, 2020, and 2021 obtained from the PUSHIDROSAL website using the Support Vector Regression (SVR) algorithm based on Cloud Computing. Therefore, the purpose of this research is to build tidal predictions in Alor, NTT which then integrates all datasets into the Cloud Computing environment to speed up data processing.parameter tuning is done with the Radial Basis Function (RBF) kernel using a gamma parameter of 1000 which produces an RMSE value of 0.0105 and a correlation of 1, so the model is considered quite good in predicting tides at the Alor pushidrosal station, East Nusa Tenggara.
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