BAREKENG: Jurnal Ilmu Matematika dan Terapan
Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan

INFLATION FORECASTS IN AMBON USING NEURAL NETWORK APPLICATIONS BACKPROPAGATION

Mozart W Talakua (Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura)
Venn Yan Ishak Ilwaru (Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura)
Berny P Tomasouw (Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura)
Syella Z Limba (Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura)



Article Info

Publish Date
01 Jun 2022

Abstract

An artificial Neural Network is the processing of information systems on certain characteristics which are artificial representations based on human neural networks. Artificial Neural Networks can be applied to various fields in human life, one of which is the economic field. In this study, the Artificial Neural Network is used to predict the inflation rate using the Backpropagation method. The data used in this study is 144 data, with 100 data as training data and 44 data as test data taken from the Central Statistics Agency of Maluku Province from 2008-2019. The best prediction accuracy level is obtained by using learning rate (a) = 0.1, Target Error = 0.000001, Maximum epoch = 500, network architecture 11-1, and 70% training data sharing scheme and 30% test data. The average absolute error percentage (MAPE) is 85.21%.

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Journal Info

Abbrev

barekeng

Publisher

Subject

Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

Description

BAREKENG: Jurnal ilmu Matematika dan Terapan is one of the scientific publication media, which publish the article related to the result of research or study in the field of Pure Mathematics and Applied Mathematics. Focus and scope of BAREKENG: Jurnal ilmu Matematika dan Terapan, as follows: - Pure ...