Auto-Regressive Integrated Moving Average (ARIMA) Forecasting for Monthly Household LPG Demand in Indonesia

EasyChair Preprint 5078

Abstract

Forecasting demand for household LPG in Indonesia, which uses this energy source as the primary commodity in people's cooking activities, is an essential policy tool used by decision-makers to make plans and decisions. Besides that, most of the initial studies related to the supply chain always put forward the demand side in determining the next policy planning steps. Based on this, a method is needed to obtain the estimated value of future LPG needs. The decision-makers that decide at this time in terms of investment, subsidy planning, and supply planning and control systems in their implementation become more appropriate and effective. Based on some studies and best practices, time series forecasting can provide better results found on these problems. This study uses the Autoregressive Integrated Moving Average (ARIMA) method to estimate household LPG demand in Indonesia. ARIMA forecasting of the total household LPG demand will provide a clearer picture of taking strategic steps later.

Keyphrases: ARIMA Forecasting, Household LPG Demand, Indonesia

@booklet{EasyChair:5078,
  author    = {Aan Nurochman and Armand Omar Moeis},
  title     = {Auto-Regressive Integrated Moving Average (ARIMA) Forecasting for Monthly Household LPG Demand in Indonesia},
  howpublished = {EasyChair Preprint 5078},
  year      = {EasyChair, 2021}}