Forecasting rainfall in Surabaya using the singular spectrum analysis method

Singular Spectrum Analysis (SSA) is a time series analysis method that uses a non-parametric approach. This study aims to determine the model and predict rainfall in Surabaya. The SSA process begins with decomposition consisting of embedding and singular value decomposition. Then a reconstruction pr...

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Hauptverfasser:	Soehardjoepri, Azmi, Ulil, Safitri, Ika, Ivan
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Eigenvectors Forecasting Mathematical models Rainfall Singular value decomposition Spectrum analysis
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creator	Soehardjoepri Azmi, Ulil Safitri, Ika Ivan
description	Singular Spectrum Analysis (SSA) is a time series analysis method that uses a non-parametric approach. This study aims to determine the model and predict rainfall in Surabaya. The SSA process begins with decomposition consisting of embedding and singular value decomposition. Then a reconstruction process is carried out, which consists of eigentriple grouping and diagonal averaging. The determination of eigentriple grouping is based on changes in the value of the eigenvectors, which do not start much different between each eigenvector. This study will compare various window length (L) values. The best model obtained is with L = 72, MAD value is 151.9903, MSE is 32340.72, and sMAPE is 0.2679602. These results indicate that the best model will be obtained when using a maximum L, which is half of the total data or as much as 72. The results of rainfall forecasting using SSA cannot be used in the long term.
doi_str_mv	10.1063/5.0183433
format	Conference Proceeding
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subjects	Eigenvectors Forecasting Mathematical models Rainfall Singular value decomposition Spectrum analysis
title	Forecasting rainfall in Surabaya using the singular spectrum analysis method
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