Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay

  • Didit Adytia School of Computing, Telkom University http://orcid.org/0000-0001-8097-5104
  • Alif Rizal Yonanta School of Computing, Telkom University
  • Nugrahinggil Subasita School of Computing, Telkom University
https://doi.org/10.21108/IJOICT.2018.42.300
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Abstract

Prediction of wind wave is highly needed to support safe navigation, especially for ship. Besides that, loading and unloading activities in a harbour, as well as for design purpose of coastal and offshore structures, data of prediction of wave height are needed. Based on its nature, the wind wave has random behaviour that is highly depending on behaviour of wind as the main driving force. In this paper, we propose a prediction method for wind wave by using Autoregressive Integrated Moving Average or ARIMA. To obtain historical data of wind wave, we perform  wave simulation by using a phase-averaged wave model SWAN (Simulating Wave Near Shore).  From the simulation, time series of wind wave is obtained. The prediction of wind wave is performed to calculate forecast of 24  hours ahead. Here, we perform wind wave prediction in a location in Jakarta Bay, Indonesia. We perform several combination of ARIMA model to obtain best fit model for wind wave prediction in the location in Jakarta Bay. Results of prediction show that ARIMA model give an accurate prediction especially for short term prediction.

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Author Biography

Didit Adytia, School of Computing, Telkom University
Didit Adytia currently works at the School of Computing, Telkom University. He does research in Applied mathematics, Ocean Engineering, and Oceanography. He is working on phase resolving models ; model developments and applications of Boussinesq & Non-hydrostatic model, and phase averaged wave model ; for hindcasting, forecasting, and Tropical Cyclone reconstruction.

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Published
2019-04-02
How to Cite
Adytia, D., Yonanta, A. R., & Subasita, N. (2019). Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay. International Journal on Information and Communication Technology (IJoICT), 4(2), 33-42. https://doi.org/10.21108/IJOICT.2018.42.300
Issue
Vol. 4 No. 2 (2018): December 2018
Section
Data Science
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