Rangkiang Mathematics Journal
Vol. 4 No. 1 (2025): Rangkiang Mathematics Journal

Artificial Neural Network Model for Forecasting Inflation Rate in Indonesia Using Backpropagation Algorithm in Indonesia

Fajrin Putra Hanifi (Unknown)
Syafriandi (Unknown)
Chairina Wirdiastuti (Unknown)
Nonong Amalita (Unknown)
Zilrahmi (Unknown)



Article Info

Publish Date
27 Apr 2025

Abstract

Inflation is defined as a general and persistent rise in prices. Stable inflation is a prerequisite for sustainable Inflation, defined as a general and persistent rise in prices. Stable inflation is a prerequisite for sustainable economic growth. The importance of controlling inflation is based on the consideration that high and unstable inflation hurts the socio-economic conditions of the community. In this context, government and economic agents must know the future inflation rate. The backpropagation algorithm forecasting method can be a mathematical tool to forecast future inflation rates. The best forecasting model is obtained from applying the backpropagation algorithm, namely ANN BP (12,2,1), with a mean square error value of 0.15 and an absolute percentage error value of 11.09%. Based on these results, the back-propagation algorithm in artificial neural networks can accurately forecast the inflation rate. Thus, it is hoped that this research can be used in economic decision-making.

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Journal Info

Abbrev

RMJ

Publisher

Subject

Mathematics Other

Description

Rangkiang Mathematics Journal (RMJ) is a prestigious vision journal which focuses on publishing research, and advance literature study in mathematics and mathematics education. The scope of this journal includes: mathematics teacher profesionalisme, Realistic Mathematics Education, ...