PERAMALAN INFLASI DI KOTA SURAKARTA MENGGUNAKAN MODEL Autoregressive Integrated Moving Average (ARIMA)

Abstract

Inflation is a problem for the whole world, both directly and indirectly which
affects the economy. The future instability of inflation in the city of Surakarta will
make it difficult for the central bank and government to determine policies. To
overcome the instability of the inflation rate, one way that can be done is to
predict time series data. The Autoregressive Integrated Moving Average
(ARIMA) method has the ability to capture the necessary information regarding
the inflation rate and is able to overcome the instability of the inflation rate. The
purpose of this study is to predict inflation in the city of Surakarta from January
2020 to December 2020 using the best ARIMA model assisted by software R.
Inflation data is taken from BPS Surakarta City from January 2010 to December
2019. ARIMA analysis is carried out in accordance with the Box-Jenkins
procedure. namely identifying data, estimating parameters and significance
testing, and determining the best ARIMA model. The results of the analysis using
R show that the best ARIMA model for forecasting inflation in Surakarta is
ARIMA (1,0,0) (2,0,0). The level of accuracy of the results of this inflation
forecast still needs to be developed with further research, such as modification of
the model which is expected to determine a more accurate forecast to ensure that
a policy step or strategy of the government and central bank related to inflation
can be managed properly.
       
Keywords : ARIMA, Inflation, Forecasting, Time Series