Implementation of Artificial Neural Networks For Predicting Percentage Growth Goat Meat Production In Indonesia

Kiki Yulianto(1), Siti Wardah(2), Taufik Baidawi(3*),

(1) Universitas Andalas, Padang, Indonesia, Indonesia
(2) Universitas Islam Indragiri, Riau, Indonesia
(3) Universitas Bina Sarana Informatika, Jakarta, Indonesia
(*) Corresponding Author

Abstract


When people are aware of the fulfillment of nutritious food, the demand for foods that are high in protein increases, such as milk, eggs, and meat. This study discusses the prediction of the percentage growth of goat meat production in Indonesia using an artificial neural network using the backpropagation method. This research data was taken from goat production data in 2016-2020. The data is taken from data from the Central Statistics Agency of Indonesia. The process uses 6 variables, namely 2015 (X1) data, 2016(X2) data, 2017(X3) data, 2018(X4) data as input data, and 2019(T) data as target data. While the testing process uses 6 variables, namely data for 2016(X1), data for 2017(X2), data for 2018(X3), data for 2019(X4) as input data, and data for 2020(T) as target data. The results of this study are predictions of the number of goat meat production data for the following year and the percentage growth of Indonesian goat meat production.

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DOI: https://doi.org/10.30645/brahmana.v5i1.274

DOI (PDF): https://doi.org/10.30645/brahmana.v5i1.274.g271

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