 Peramalan Harga Emas Saat Pandemi Covid-19 Menggunakan Model Hybrid Autoregressive Integrated Moving Average - Support Vector RegressionJambura J. Math. and Drajat Indra Purnama No mdu3z, OSF Preprints from Center for Open Science Abstract: Gold investment is one of the favorite investments during the Covid 19 pandemic as it is today. This is because the price of gold is relatively volatile but shows an increasing trend. Investors are required to be smart in investing in gold, able to predict future opportunities. One of the time series data forecasting models is the Autoregressive Integrated Moving Average (ARIMA) model. The ARIMA model is good for use on linear patterned data but if it is used on nonlinear data the accuracy decreases. To solve the problem of nonlinear data, you can use the Support Vector Regression (SVR) model. The linearity test on the gold price data shows that there are linear and nonlinear data patterns at the same time so that a combination of ARIMA and SVR is used, namely the ARIMA-SVR hybrid model. Forecasting results using the ARIMA-SVR hybrid model show better results than the ARIMA model. This is evidenced by the MAPE value of the ARIMA-SVR hybrid model which is smaller than the MAPE value of the ARIMA model. The MAPE value of the ARIMA-SVR hybrid model is 0.355 on the training data and 4.001 on the testing data, while the MAPE value of the ARIMA model is 0.903 in the training data and 4.076 in the testing data. Date: 2021-01-01 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:mdu3z Access Statistics for this paper More papers in OSF Preprints from Center for Open Science |
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