IJID (International Journal on Informatics for Development)
Vol. 13 No. 1 (2024): IJID June

Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production

Tundo (Unknown)
Rachmat Hidayat Insani (Unknown)
Rasiban (Unknown)
Untung Suropati (Unknown)



Article Info

Publish Date
17 Oct 2024

Abstract

Beef is considered a high-value commodity as it is an important source of protein. Interest in beef continues to rise. Beef production has risen sharply in the past decade, but declined by 7,240.68 tons in 2020 amid coronavirus lockdowns. After that, in 2021, production reached 16,381.81 tons and continued to increase in 2022 and 2023. A precise method is required to forecast beef production. One way to predict beef production in Jakarta is using the Single Exponential Smoothing and Double Moving Average methods. The two algorithms are compared to get the lowest error rate. The methodology used in this research is the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology. According to SAS Institute Inc., there are five stages in developing a system using the SEMMA methodology. After analyzing using MAPE, it is found that the algorithm with the smallest error value is the Single Exponential Smoothing algorithm with a percentage in the monthly period of 16% while for the annual period, it is 27% compared to other algorithms. The forecasting is quite accurate because the MAPE value for each algorithm used has an error of less than 31%.

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Journal Info

Abbrev

ijid

Publisher

Subject

Computer Science & IT

Description

One important point in the accreditation of higher education study programs is the availability of a journal that holds the results of research of many investigators. Since the year 2012, Informatics Department has English language. Journal called IJID International Journal on Informatics for ...