HYBRID MODEL OF SINGULAR SPECTRUM ANALYSIS WITH AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND FUZZY TIME SERIES FOR INDONESIAN CRUDE PRICE FORECASTING

  • Etik Zukhronah Statistics Study Program, Faculty of Mathematics and Natural Science, Universitas Sebelas Maret, Indonesia https://orcid.org/0000-0001-6387-4483
  • Winita Sulandari Statistics Study Program, Faculty of Mathematics and Natural Science, Universitas Sebelas Maret, Indonesia https://orcid.org/0000-0002-8185-1274
  • Esa Permata Sari Putri Ilahi Statistics Study Program, Faculty of Mathematics and Natural Science, Universitas Sebelas Maret, Indonesia
Keywords: ARIMA, FTS, Hybrid model, ICP, SSA

Abstract

This study discusses a hybrid model of Singular Spectrum Analysis (SSA) with Autoregressive Integrated Moving Average (ARIMA) and Fuzzy Time Series (FTS) for forecasting the Indonesian Crude Price (ICP). SSA is considered to capture the deterministic component of the data while the ARIMA and FTS are to represent the stochastics one. The data that used in this study are ICP per month from January 2017 to May 2023. The data from January 2017 to December 2022 are used as insample data, while the data from January to May 2023 are used as outsample data. The insample data is firstly modeled by SSA and the residuals are then modeled by ARIMA, referred to as the hybrid SSA-ARIMA. By the same procedure, the hybrid SSA-FTS model is also constructed to the insample data. Based on the experiment, the hybrid SSA-ARIMA produces Mean Absolute Percentage Error values 8.08% for an insample and 7.10% for an outsample data. These values are less than those obtained by hybrid SSA-FTS. Therefore, the hybrid SSA-ARIMA is recommended for forecasting the monthly ICP.

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Published
2024-07-31
How to Cite
[1]
E. Zukhronah, W. Sulandari, and E. Ilahi, “HYBRID MODEL OF SINGULAR SPECTRUM ANALYSIS WITH AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND FUZZY TIME SERIES FOR INDONESIAN CRUDE PRICE FORECASTING”, BAREKENG: J. Math. & App., vol. 18, no. 3, pp. 1519-1526, Jul. 2024.