Comparison of Forecasting Techniques Moving Average and Double Exponential Smoothing in Sugar Production for Enhanced Maintenance Preparedness Ahead of Milling Season

Abstract

Sugar as a commodity has a very vital role, not only being a basic need for Indonesian society, but also an inseparable element in various industrial sectors. The aim of this research is to compare sugar production forecasting systems by comparing two methods using moving averages and double exponential smoothing (holt's method). Forecasting is the process of projecting or predicting future events with a structured planning approach. Forecasting in sugar production is needed to find out whether the next month can meet the target or not. The amount of sugar production is used as a reference for carrying out maintenance which is carried out before the arrival of the milling season. The research results show that both forecasting methods have their respective strengths and weaknesses. The results of this research showed that the double exponential smoothing method (Holt's method) provided better values ​​than the moving average. Highlights: Sugar production forecasting aids in maintenance planning. Comparison between moving averages and double exponential smoothing methods enhances predictive accuracy. The study reveals the superiority of Holt's method in sugar production forecasting. Keywords: Forecasting, Moving Average, Double Exponential Smoothing, Sugar Production