ARIMA MODEL OF OUTLIER DETECTION FOR FORECASTING CONSUMER PRICE INDEX (CPI)

  • M. Imron Study Program of Mathematics, Faculty of Science and Technology, UIN Sunan Ampel Surabaya
  • Wika Dianita Utami Study Program of Mathematics, Faculty of Science and Technology, UIN Sunan Ampel Surabaya
  • Hani Khaulasari Study Program of Mathematics, Faculty of Science and Technology, UIN Sunan Ampel Surabaya
  • Firman Armunanto Badan Pusat Statistik (BPS) Indonesia of Probolinggo
Keywords: Consumer Price Index (CPI), Forecasting, ARIMA, Outlier Detection

Abstract

The Consumer Price Index (CPI) is a indicator used by Badan Pusat Statistik (BPS) which describes the average change in the prices paid by urban consumers for a market basket of consumer goods and services in a certain period. The case on Consumer Price Index (CPI) of Probolinggo City, if the Consumer Price Index (CPI) increase then describe inflation occurs and conversely. The Consumer Price Index (CPI) of Probolinggo City increase is not fixed. This study is to forecast the Consumer Price Index (CPI) that the results can be used as one of the considerations in carrying out economic development in the future. Research focused on the data of Consumer Price Index (CPI) of Probolinggo City from January 2014 to April 2022. Methodology implemented in this study is Autoregressive Integrated Moving Average (ARIMA). Result show that ARIMA  without an outlier was the best model for predicting Consumer Price Index (CPI) of Probolinggo City for the next 8 months. This model shows the value of MAPE is The value of forecasting results in each month has decreased and increased not so significantly where in May 2022 the forecasting value was 108,391 then in June 2022 the forecasting value became 108,411 and so on until December 2022 the forecasting results using ARIMA model   of 107,845.

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Published
2022-12-15
How to Cite
[1]
M. Imron, W. Utami, H. Khaulasari, and F. Armunanto, “ARIMA MODEL OF OUTLIER DETECTION FOR FORECASTING CONSUMER PRICE INDEX (CPI)”, BAREKENG: J. Math. & App., vol. 16, no. 4, pp. 1259-1270, Dec. 2022.