Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA)
Main Authors: | Lubis, Deltha Airuzsh, Johra, Muhamad Budiman Johra, Darmawan, Gumgum Darmawan |
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Other Authors: | Departemen Statistika FMIPA UNPAD |
Format: | Article info application/pdf Journal |
Bahasa: | eng |
Terbitan: |
Matematika UIN Sunan Ampel Surabaya
, 2017
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Subjects: | |
Online Access: |
http://mantik.uinsby.ac.id/index.php/Mantik1/article/view/54 http://mantik.uinsby.ac.id/index.php/Mantik1/article/view/54/pdf |
Daftar Isi:
- Consumer Price Index (CPI) are the indicators used to measure the inflation and deflation of a group of goods and services in general. Forecasting CPI to be important as early detection in facing price hikes. This study uses the SSA and SARIMA. SARIMA a parametric model that requires various assumptions while SSA is a nonparametric technique that is free from a variety of assumptions, but both methods require seasonal patterns in the data. Based on the research results, methods of SSA with length window(L) of 24 and a grouping of 4 (1 group of seasonal and 3 groups of trends) and SARIMA models of order (0,1,1), (0,1,1) 6 is the most accurate and reliable models in forecasting CPI to the value Padang Sidempuan City. Forecasting CPI Padangsidimpuan City for the next 5 months with SSA method and SARIMA (0,1,1), (0,1,1) 6 shows the pattern of a trend is likely to increase but forecasting the 5th month with SSA method showed a surge in the value of CPI high or high inflation will occur.