Title :
Optimization of neural network using genetic algorithm in forecasting third party funds bank
Author :
Purba, Imelda ; Permanasari, Adhistya Erna ; Setiawan, Noor Akhmad
Author_Institution :
Dept. of Inf. Technologyand Elektronics Eng., Gadjah Mada Univ. (UGM), Yogyakarta, Indonesia
Abstract :
Forecasting is an activity to predict something that has not happened. In the economic sector, banks have the greatest effect on the economy of a country. Sources of bank funds that contribute to the operational activities or lending is third party funding. The third party funding is consist of savings, giro and deposits. The higher the ratio of third party funding, its mean the better public confidence in that bank. It is also a source of income for banks. This study will predict revenue third party funding using artificial neural network (ANN) and genetic algorithm. Forecasting using ANN and genetic algorithms able to provide forecasting results with minimal error.
Keywords :
banking; economics; forecasting theory; genetic algorithms; neural nets; ANN; artificial neural network; economic sector; genetic algorithm; optimization; revenue third party funding; third party funds bank forecasting; Artificial neural networks; Banking; Genetics; IEEE Potentials; artificial neural network; forecasting; genetic algorithms; neural networks;
Conference_Titel :
Electrical Engineering and Informatics (MICEEI), 2014 Makassar International Conference on
Print_ISBN :
978-1-4799-6725-4
DOI :
10.1109/MICEEI.2014.7067336