JOIN (Jurnal Online Informatika)
Vol 5 No 1 (2020)

Prediction of Indonesian Inflation Rate Using Regression Model Based on Genetic Algorithms

Faisal Dharma (Universitas Gadjah Mada)
Shabrina Shabrina (Universitas Gadjah Mada)
Astrid Noviana (Universitas Gadjah Mada)
Muhammad Tahir (Universitas Gadjah Mada)
Nirwana Hendrastuty (Universitas Gadjah Mada)
Wahyono Wahyono (Universitas Gadjah Mada)



Article Info

Publish Date
16 Jul 2020

Abstract

Inflation occurs where there is an increase in the price of goods or services in general and continuously in a country. Uncontrolled inflation will have an impact on the decline of the Indonesian economy. Therefore, the prediction of future inflation levels is necessary for the government to develop economic policies in the future. Prediction of inflation levels can be done by studying historical past Consumer Price Index (CPI) data. Regression methods are often used to solve prediction problems. The problem of finding the optimal prediction model can be seen as an optimization problem. Genetic algorithms are often used to deal with optimization problems. Thus, this work proposed to use a genetic algorithm-based regression model for predicting inflation levels. The model was trained and evaluated using real CPI data which obtained from the Indonesian Central Bank. Based on the experiment, it is proved that the proposed model is effective in predicting the inflation level as it gains MSE of 0.1099.

Copyrights © 2020






Journal Info

Abbrev

join

Publisher

Subject

Computer Science & IT

Description

JOIN (Jurnal Online Informatika) is a scientific journal published by the Department of Informatics UIN Sunan Gunung Djati Bandung. This journal contains scientific papers from Academics, Researchers, and Practitioners about research on informatics. JOIN (Jurnal Online Informatika) is published ...