Non-stationary time series data for natural rubber inventory forecasting: A case study

Abstract

PPLK Corp. is a company that uses natural rubber as the main raw material to produce crumb rubber. The problem identified in PPLK Corp. is the insufficient amount of natural rubber received to produce and fulfill consumer demand. There have been fluctuations in the amount of natural rubber received and high variability between periods. To minimize this variability, it is necessary to forecast natural rubber requirements. The purpose of this study is to forecast the natural rubber inventory for the next periods using the best-fitted model, which is the Autoregressive Integrated Moving Average (ARIMA) method. A total of 547 daily data points from 2021 to 2022 were used. As a result, the ARIMA (1,1,2) model was found to be the best model for natural rubber forecasting in the rubber factory. The ARIMA (1,1,2) model had the smallest AIC value compared to others. The total daily natural rubber need is forecasted to be around 67.588 kilograms with a range between 64.805 and 70.421 kilograms per day. However, it should be noted that this study was limited to short-term forecasting only.