Forecasting Analysis of Organic Red Rice’s Demand Using Artificial Neural Networks

  • Abdul Holik Agribusiness Department, Politeknik Negeri Banyuwangi
  • Riza Rahimi Bachtiar Agribusiness Department, Politeknik Negeri Banyuwangi
  • Shinta Setiadevi Agribusiness Department, Politeknik Negeri Banyuwangi

Abstract

Consumer demand for organic red rice in Banyuwangi is always fluctuating each period. This study aims to design an Artificial Neural Network (ANN) Architecture and forecast the demand of Red Rice Production at PT. Sirtanio Organik Indonesia located at Singojuruh, Banyuwangi. Demand forecasting is the level of demand product that is expected to be realized for a certain period in the future. The data used as input for this study are product prices, stocks, sales and demand in 2015-2017. This research used six architectures and Algorithm that used is Artificial Neural Network Backpropagation. The research result showed that highest demand for organic red rice is in August of 2018 and the lowest in April of 2018. The conclusion of this research showed that the best architecture is 3-20-1 with MSE value of 0.002 and R squared of 0.859 and this model is well used to predict organic red rice demand in Banyuwangi.

Keywords: Artificial Neural Network, backpropagation, Banyuwangi, MSE, organic red rice

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Author Biography

Shinta Setiadevi, Agribusiness Department, Politeknik Negeri Banyuwangi
Agribusiness Department
Published
2019-07-27
How to Cite
Holik, A., Bachtiar, R. R., & Setiadevi, S. (2019). Forecasting Analysis of Organic Red Rice’s Demand Using Artificial Neural Networks. Jurnal Manajemen & Agribisnis, 16(2), 123. https://doi.org/10.17358/jma.16.2.123