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1 Pertemuan 24 Deret Berkala, Peramalan, dan Angka Indeks-2 Matakuliah: A0064 / Statistik Ekonomi Tahun: 2005 Versi: 1/1.

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Presentasi berjudul: "1 Pertemuan 24 Deret Berkala, Peramalan, dan Angka Indeks-2 Matakuliah: A0064 / Statistik Ekonomi Tahun: 2005 Versi: 1/1."— Transcript presentasi:

1 1 Pertemuan 24 Deret Berkala, Peramalan, dan Angka Indeks-2 Matakuliah: A0064 / Statistik Ekonomi Tahun: 2005 Versi: 1/1

2 2 Learning Outcomes Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu : Menghubungkan beberapa deret berkala bagi penyusunan aangka indeks, peramalan dengan menggunakan metode rata-rata bergerak, dan exponential smoothing

3 3 Outline Materi Metode Rata-rata Bergerak Metode Exponential Smoothing Angka Indeks

4 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Forecasting a Multiplicative Series: Example 12-3

5 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Multiplicative Series: Review

6 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Smoothing is used to forecast a series by first removing sharp variation, as does the moving average. Exponential smoothing is a forecasting method in which the forecast is based in a weighted average of current and past series values. The largest weight is given to the present observations, less weight to the immediately preceding observation, even less weight to the observation before that, and so on. The weights decline geometrically as we go back in time Lag W e i g h t Weights Decline as We Go Back in Time and Sum to 1 Weights Decline as we go back in Time Weight Lag 12-5 Exponential Smoothing Methods

7 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., The Exponential Smoothing Model

8 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., DayZw=.4w= * DayZw=.4w= * Original data: Smoothed, w=0.4: Smoothed, w=0.8: Day w =. 4 Exponential Smoothing: w=0.4 and w=0.8 Example 12-4

9 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Example 12-4 – Using the Template

10 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., An index number is a number that measures the relative change in a set of measurements over time. For example: the Dow Jones Industrial Average (DJIA), the Consumer Price Index (CPI), the New York Stock Exchange (NYSE) Index Index Numbers

11 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Index Index Year Price 1984-Base 1991-Base Index Index Year Price 1984-Base 1991-Base Year P r i c e Price and Index (1982=100) of Natural Gas Price Original Index (1984) Index (1991) Index Numbers: Example 12-5

12 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Example 12-6: Adjusted YearSalarySalary Example 12-6: Adjusted YearSalarySalary C P I Year Consumer Price index (CPI): 1967=100 Consumer Price Index – Example 12-6

13 COMPLETE 5 t h e d i t i o n BUSINESS STATISTICS Aczel/Sounderpandian McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Example 12-6: Using the Template

14 14 Penutup Deret Berkala pada dasarnya bertujuan untuk mengidentifikasi faktor-faktor atau komponen deret berkala (trend, variasi musim, perilaku siklus dan variasi lainnya) yang selanjutnya digunakan sebagai landasan untuk meramalkan nilai-nilai tersebut di masa mendatang


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