17
Tabel
2.1
menunjukkan beberapa
teknik
peramalan
yang
dapat
digunakan
berdasarkan pola datanya.
Tabel 2.1 Berbagai Metode Peramalan
Pola Data
Metode
Stationary
Naive Methods
Simple Averaging Methods
Moving Averages
Autoregressive Moving Average (ARIMA) models / Box-Jenkins Methods
Trend
Holt's Linear Exponential Smoothing
Simple Regression
Growth Curves
Exponential models
Autoregressive Moving Average (ARIMA) models / Box-Jenkins Methods
Seasonal
Classical Decomposition
Censux X-12
Winter's Exponential Smoothing
Multiple Regression
Autoregressive Moving Average (ARIMA) models / Box-Jenkins Methods
Cyclical
Classical Decomposition
Economic Indicators
Econometric models
Multiple Regression
Autoregressive Moving Average (ARIMA) models / Box-Jenkins Methods
Sumber: Hanke (2005, p75-76)
2.1.4.1 Exponential Smoothing
Exponential smoothing memberikan bobot secara eksponential kepada data yang
diobservasi. Data yang paling baru mendapatkan bobot paling besar a (alpha) (dimana 0
<
a
<
1), data sebelumnya mendapatkan bobot lebih sedikit a(1- a), dua data sebelumnya
mendapatkan bobot lebih sedikit lagi a(1- a)² dan seterusnya.
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