Open AccessForecasting Inflation Using Seasonal Autoregressive Integrated Moving Average Method for Estimates Decent Living Costs
Author(s) -
R Fahrudin,
Irfan Dwiguna Sumitra
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/662/2/022062
Subject(s) - autoregressive integrated moving average , inflation (cosmology) , econometrics , autoregressive model , value (mathematics) , moving average , inflation rate , statistics , economics , time series , mathematics , macroeconomics , monetary policy , physics , theoretical physics
This research purposes to forecast inflation data. The forecasting results can be used as a reference for the determination of decent living costs for a single worker in one month. The method used in this study is the SARIMA method, in forecasting the inflation rate where the data is time series. SARIMA method can show forecasting results that are able to follow the movement of the actual data from the inflation rate. Based on the comparison of overall SARIMA model and with a value of MAD, MSE and MAPE smallest, it shows the results of forecasting the SARIMA method on inflation values are very feasible and accurate. The result KHL value with calculation results of inflation forecasting has a value close to actual data so that the value can be used as a reference for decision making a single worker in needing one month.