Sulfuric Acid Demand Forecasting Analysis Using Double Moving Average and Double Exponential Smoothing Methods at PT Petrokimia Gresik

Putri, Triana Oktavia (2025) Sulfuric Acid Demand Forecasting Analysis Using Double Moving Average and Double Exponential Smoothing Methods at PT Petrokimia Gresik. G-Tech: Jurnal Teknologi Terapan, 9 (1). pp. 19-28. ISSN 2623-064X

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Abstract

PT Petrokimia Gresik is the most complete fertilizer producer in Indonesia, offering a wide range of fertilizers and non-fertilizers for agro-industrial solutions. One of its key non-fertilizer products is Sulfuric Acid. In planning future production, forecasting sales demand is the first crucial step. However, the company faces a challenge with inconsistencies between sales forecasts and actual sales of Sulfuric Acid. Discrepancies between forecasted and actual sales can lead to significant differences, impacting production planning and inventory management. To address this issue, this studyaims to identify the most effective demand forecasting method. The study considers two alternative forecasting methods: Double Moving Average and Double Exponential Smoothing. Using a quantitative approach, with data collected through field observations, the study finds that the Double Exponential Smoothing method, with a smoothing constant (α) of 0.2, results in the lowest error rate. The Mean Absolute Deviation (MAD), which measures the average absolute difference between actual and forecasted sales, is 1.0185. Additionally, the Mean Squared Error (MSE), which gives more weight to larger errors through squaring, is calculated as 1.25681. Based on these results, the study recommends the Double Exponential Smoothing method as the most effective forecasting tool for the company.

Item Type:	Article
Uncontrolled Keywords:	Forecasting, Double Moving Average, Double Exponential Smoothing, MAD, MSE
Subjects:	Engineering > Industrial Engineering Engineering
Divisions:	Faculty of Engineering > Industrial Engineering Study Program
Depositing User:	Triana Oktavia Putri
Date Deposited:	17 Mar 2025 03:53
Last Modified:	17 Mar 2025 03:53
URI:	http://eprints.umg.ac.id/id/eprint/12443

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