Polak-Ribiere updates analysis with binary and linear function in determining coffee exports in Indonesia

Abstract

The purpose of this study is to determine and predict coffee exports in Indonesia based on the main destination countries for years to come. The results of this study are expected to be widely used for both government and private sector as an evaluation material in coffee, economic and business development. The data used in this study is Coffee Exports In Indonesia based on the main destination countries in 2006-2015. Data processed from customs documents of the Directorate General of Customs and Excise cited from Indonesia Statistics Publication. This research uses artificial neural network Polak-Ribiere updates which will be combined with bipolar activation function and linear function. The architectural model used there are 4, among others: 8-10-15-1, 8-15-10-1, 8-15-30-1 and 8-30-15-1. The best architectural model of the 4 models used is 8-10-15-1 with error rate of 0.001-0.06, alpha = 0.001, beta = 0.1, delta = 0.01 and gama = 0.1. The resulting accuracy is 86%.