Open AccessPemodelan Dan Peramalan Indeks Harga Konsumen (IHK) Kota Sampit Dengan Seasonal Arima (Sarima)
Author(s) -
Agustina Elisa Dyah Purwandari
Publication year - 2020
Publication title -
jurnal derivate/jurnal derivat
Language(s) - English
Resource type - Journals
eISSN - 2549-2616
pISSN - 2407-3792
DOI - 10.31316/j.derivat.v6i2.497
Subject(s) - autoregressive integrated moving average , inflation (cosmology) , economics , econometrics , consumer price index (south africa) , price index , seasonal adjustment , inflation rate , central bank , autoregressive model , time series , statistics , monetary policy , mathematics , monetary economics , mathematical analysis , physics , variable (mathematics) , theoretical physics
ampit is one of 82 cities in Indonesia which calculate inflation. Inflation is an increase of prices on goods and services in a region. Government’s control is very important because inflation relates to the real income, the exchange rate, import exports, and so on. Inflation is based on the Consumer Price Index (CPI). Because of CPI is a monthly data prices, it is highly influenced by seasonal factors. Therefore, CPI data modelling is needed because it helps the government to make appropriate policies. Method that can be used for time series data with seasonal influences is Seasonal Autoregressive Integrated Moving Average (SARIMA). The results of the study show that the right model for Sampit’s CPI is SARIMA with the order p = 1, d = 1, P = 1, D = 1, Q = 1, s = 12. It is the best model that can built and be used for forecasting because with 95 percent of confidence, the model explains 87.23 percent of data. Forecasting in this research use interval analysis and found that January 2020 may be the highest increase of CPI (inflation) in 2020. Keywords: CPI, Inflation, SARIMA