• DocumentCode
    3581552
  • 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
  • fYear
    2014
  • Firstpage
    184
  • Lastpage
    188
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering and Informatics (MICEEI), 2014 Makassar International Conference on
  • Print_ISBN
    978-1-4799-6725-4
  • Type

    conf

  • DOI
    10.1109/MICEEI.2014.7067336
  • Filename
    7067336