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All Journal Indonesian Journal of Computer Science and Engineering
Onyekachukwu Godspower Ekwueme
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Demand Forecasting of Domestic Gas Consumption: A Comparative Study of Trend Analysis, Moving Average, Single and Double Exponential Smoothing Methods Uchendu Onwusoronye Onwurah; Chukwuebuka Martinjoe U-Dominic; Christopher Chukwutoo Ihueze; Onyekachukwu Godspower Ekwueme; Obiora Jeremiah Obiafudo; Emmanuel Okechukwu Chukwumuanya
Indonesian Journal of Computer Science and Engineering Vol. 2 No. 01 (2025): IJCSE Volume 02 Nomor 01, Mei 2025
Publisher : CV. Cendekiawan Muda Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70656/ijcse.v2i01.429

Abstract

The increase in population and global economy has led to an increase in energy demand and consumption. Domestic gas consumption has continued to increase on a daily basis. Forecasting is essential to support decisions such as inventory management, production planning, and procurements in natural gas production and distribution. This study is aimed at forecasting natural gas demand in a selected area using trend analysis, moving average, single exponential smoothing, and double exponential smoothing techniques. 16 years (2009–2024) historical data were collected from a domestic gas distribution plant. The data were analyzed, and forecasts were made using trend analysis, moving average, single exponential smoothing, and double exponential methods. A comparative study revealed that trend analysis outperformed the other forecasting techniques, based on the lowest mean absolute percentage error (MAPE), mean absolute deviation (MAD), and mean squared deviation (MSD) as the decision criteria. The performance of double exponential smoothing is very close to that of the trend analysis. This study concludes that both trend analysis and double exponential smoothing, based on their lower MAPE and MAD, can be adopted by the gas plant in forecasting the domestic gas demand in the selected area.
Co-Authors Christopher Chukwutoo Ihueze Chukwuebuka Martinjoe U-Dominic Emmanuel Okechukwu Chukwumuanya Obiora Jeremiah Obiafudo Uchendu Onwusoronye Onwurah