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Anjar Wanto
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JOMLAI: Journal of Machine Learning and Artificial Intelligence
Published by Yayasan Literasi Sains Indonesia
ISSN : 28289102     EISSN : 28289099     DOI : 10.55123/jomlai
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well as an overview of the development of theories, methods, and related applied sciences. Topics cover the following areas (but are not limited to): Software engineering Hardware Engineering Information Security System Engineering Expert system Decision Support System Data Mining Artificial Intelligence System Computer network Computer Engineering Image processing Genetic Algorithm Information Systems Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Other relevant study topics Noted: Articles have primary citations and have never been published online or printed before
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 91 Documents
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Comparison of Weighted Moving Average and Single Exponential Smoothing Forecasting on Manila Duck Eggs Production Gusman Simon
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 5 No. 1 (2026): Maret 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v5i1.7846

Abstract

As a waterfowl, the Manila duck is a potential livestock option and a source of animal protein for the community. Its population growth is still considered low, and its egg production capacity only serves to support the food supply. Population growth and public awareness of the importance of nutrition drive the demand for animal protein consumption. The highest growth in duck egg consumption was observed between 2014 and 2018. In 2021 and 2022, the production and consumption of Manila duck eggs increased per capita every week. However, in 2024, the production rate of Manila duck eggs decreased. One way to anticipate the risk of declining Manila duck egg production is through predictive analysis. Based on the data patterns obtained from the Central Statistics Agency, the weighted moving average (WMA) forecasting method and single exponential smoothing (SES) were selected. The MAPE value of the WMA method for the last two periods 6.742%, last three periods 6.444%, and last four periods 6.814%. The MAPE value of the SES method is 6.466%. The lowest MAPE value is from the 3-period WMA method. To minimize the MAPE value, the Solver add-in application attached in MS Excel is used to determine the weight value of each period in the WMA method, as well as the smoothing coefficient value of the SES method.

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