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Dewi Sukmawati, Chandra
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Prediction of Tides in the Gisik Cemandi Coastal Area Using the Support Vector Regression (SVR) Method Dewi Sukmawati, Chandra; Novitasari, Dian Candra Rini; Dewi, Ratna Cintya
Journal of Information Technology and Computer Science Vol. 10 No. 3: Desember 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025103790

Abstract

This study was conducted to predict tidal fluctuations in the coastal area of Gisik Cemandi Village, Sidoarjo, using the Support Vector Regression (SVR) method. The dataset consisted of  time series records of sea level height for the period of March . The prediction process was implemented by testing three SVR kernel types, namely linear, polynomial, and Gaussian Radial Basis Function (RBF), along with variations of the parameters Cost , Gamma , and epsilon . Based on the evaluation using Mean Absolute Percentage Error ( MAPE), the Linear kernel demonstrated the best predictive performance with the lowest MAPE value of  under a  train-test split. The prediction results with the Linear kernel closely matched the actual data, indicating the model’s accuracy and reliability in capturing the linear patterns of tidal data. This model can be utilized as a supporting tool for tidal prediction to aid coastal activities such as navigation and fisheries.
Co-Authors Dewi, Ratna Cintya Sari, Dian Candra Rini Novita