Aplikasi Metode Singular Spectral Analysis (SSA) dalam Peramalan Pertumbuhan Ekonomi Indonesia Tahun 2017 - Rina Sri Kalsum Siregar; Dina Prariesa; Gumgum Darmawan (Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya, 2017)
The purpose of this study was to look at seasonal patterns in the data of Gross Domestic Product (GDP) quarterly in the year 2000-2016 and the implementation of Singular Spectral Analysis (SSA) in the data of GDP to predict the data of GDP in 2017. The SSA method used is the method of recurrent forecasting with bootstrap confidence interval to look at its beliefs of the interval. The source of data derived from the data of GDP in 2000-2016 with the base year in 2000 compiled by the Central Statistics Agency (CSA). The results showed that the SSA method can be used as a reliable method and can be valid that view from the value of MAPE size is 0.82 and the size of the tracking signal at -4.00.