Forecasting the Value of Oil and Gas Exports in Indonesia using ARIMA Box-Jenkins

Ansari Saleh Ahmar (Department of Statistics, Universitas Negeri Makassar, Makassar, 90223, Indonesia)
Miguel Botto-Tobar ((1) Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands (2) Research Group in Artificial Intelligence and Information Technology, University of Guayaquil, 090510, Guayaquil, Ecuador)
Abdul Rahman (Department of Mathematics, Universitas Negeri Makassar, Makassar, 90223, Indonesia)
Rahmat Hidayat (Department of Information Technology, Politeknik Negeri Padang, Limau Manis, Padang, 25164, Indonesia)

JINAV: Journal of Information and Visualization
Vol. 3 No. 1 (2022)

The objective of the study was to forecast the value of oil and gas exports in Indonesia using the ARIMA Box-Jenkins. With this prediction, it is hoped that it can be a study for future policy making. This oil and gas export data is obtained from the Indonesian Central Bureau of Statistics (BPS) website, in raw data from January 2010 to March 2022. This data is predicted using the ARIMA method with the help of R software. The stages of data analysis with ARIMA include: data stationary test, build the model indication, parameter estimation and significance test, and residual diagnostic test of the model. The results of data analysis conducted in this study show that there are 3 indications of models that were generated, namely ARIMA(1,1,0); ARIMA(0,1,1); and ARIMA(1,1,0). From these 3 model indications, the best model was ARIMA(0,1,1) with AIC value of 2047.65.