PERAMALAN PADA RUNTUN WAKTU DENGAN POLA TREND MENGGUNAKAN SSA-LRF

Singular Spectrum Analysis-Linear Recurrent Formulae (SSA-LRF) is a forecasting method that starts by decomposing time series data into several independent and interpretable components. SSA-LRF does not have any assumptions must be fulfilled thus it more flexible to use. In this research, an empirical study of has trend pattern will carried out using without difference transformation with transformation. A performed because the pattern. Although there are no met in SSA-LRF, expected produce better accuracy than process. There three used research. The first from Wei's book (2006), called W8 simulation data. second number railway passengers Java region. third Mauna Loa atmospheric CO2 concentration obtained R software. Forecasting on all resulted accurate values, improved values