Modeling and Predicting Galangal Production in Indonesia :ARIMA Approach

Abstract

This article aims to model and predict the Galangal production in Indonesia. As it is known, Galangal provides many benefits in the health sector as well as being a trading commodity both inside and outside of Indonesia. The model in this article is the ARIMA model (Auto Regressive Integrated Moving Average), that is one of the time series analysis used to model the dependent variable without including the exogenous/independent variables in the model. 23 data were used, namely the annual data of Galangal production in Indonesia from 1997 until 2019 which was published on the BPS website (Central Bureau of Statistic in Indonesia). The parameter tests, diagnostic tests, and AIC checks had been carried out on each model before. The best ARIMA model results for the transformation of natural algorithms data is the ARIMA model (0,2,1) and an exponential transformation is performed to obtain the customization and prediction data from the model. The MAPE from this model is 8% with the prediction results of Galangal production in Indonesia in 2021 is about 85478.035 ton.