Artificial Neural Network Model Application for Validating and Predicting Ruminant Population in East Java, Indonesia

Khusna, A. and Muzayyanah, M.A.U. and Kusumastuti, T.A. and Putra, A.R.S. (2024) Artificial Neural Network Model Application for Validating and Predicting Ruminant Population in East Java, Indonesia. In: IOP Conference Series: Earth and Environmental Science.

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Abstract

The aim of this study was to develop a model that could estimate the population of ruminants (beef cattle, goats, and sheep) in East Java with high accuracy. Secondary data on ruminant livestock populations in 31 regencies in East Java Province were acquired from the Central Bureau of Statistics of East Java between 2009 and 2020. Modeling backpropagation neural networks and feedforward learning processes with architectural models for beef cow population 11-3-1, goat population 11-3-1, and sheep population 11-5-1 are used to predict the population of ruminants in East Java. This architecture has a precision of more than 90. The prediction RSquared (R2) for the beef cattle population is 0.997, the goat population is 0.998, and the sheep population is 0.975. © Published under licence by IOP Publishing Ltd.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 0; All Open Access, Gold Open Access
Subjects: S Agriculture > SF Animal culture
Divisions: Faculty of Animal Sciences > Department of Livestock Socio-Economics
Depositing User: Wirasto Wirasto
Date Deposited: 02 Jun 2025 07:44
Last Modified: 02 Jun 2025 07:44
URI: https://ir.lib.ugm.ac.id/id/eprint/18707

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