Prediction of Regional Economic Growth in East Kalimantan using Genetic Algorithm - Emmilya Umma Aziza Gaffar (International Journal of Computing and Informatics (IJCANDI), 2016)
This paper outlines and presents the development of genetic algorithms (GA) that are used for analyzing and predicting Regional Economic Growth (REG) with an agriculture share (SA) and an industry share (SI) as independent variables covers 13 districts/cities in East Kalimantan Province of 2002-2012 datasets. The genetic algorithm (GA) was used for modeling of REG datasets. The results of experiment shows that GA was produced prediction value of 92.389. This results indicate that the average price fluctuation is decreased in 2012. Meanwhile, the southern region is significantly increased in 2013. The results indicated that GA was good algorithm for prediction of REG. This paper is concluded by recommending some future works that can be applied in order to improve the prediction accuracy.