CONVOLUTIONAL LSTM FOR EGG PRICES FORECASTING IN INDONESIA’S HIGH STUNTING PREVALENCE PROVINCE

Keywords: Egg Price, ConvLSTM, SDGs, Stunting

Abstract

The Sustainable Development Goals (SDGs) are a series of 17 goals fixed by the United Nations and adopted by 193 countries in 2015, including Indonesia. By 2030, to end all forms of malnutrition, targeting on stunting and wasting in children under 5 years of age is one of the targets from Goals Number 2. One affordable source of protein and nutrition used as a solution to overcome malnutrition problems such as stunting is eggs. Egg price modeling was carried out to see the affordability of prices for the community. Weekly dataset of egg price in NTT Province from 2018 to 2023 used to modeling with Convolutional LSTM. The Convolutional LSTM components are Adam optimizer, ReLU activation function, Huber loss function, with batch size and neurons of 32. The MAPE value obtained from the model is relatively small, with MAPE for training, validation, and testing of 1.97%, 1%, and 1.19% respectively. The results of egg price forecasting for December 11, 2023, to January 8, 2024, show that egg prices tend to continue to decline per week. Thus, a decrease in egg prices can be a good thing in providing more affordable nutrition for the community.

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Published
2025-01-13
How to Cite
[1]
S. Pangastuti, M. Agam, A. Santika, and J. Rosadi, “CONVOLUTIONAL LSTM FOR EGG PRICES FORECASTING IN INDONESIA’S HIGH STUNTING PREVALENCE PROVINCE”, BAREKENG: J. Math. & App., vol. 19, no. 1, pp. 281-290, Jan. 2025.