• DocumentCode
    1950108
  • Title

    Prediction system of economic crisis in Indonesia using time series analysis and system dynamic optimized by genetic algorithm

  • Author

    Sa´adah, Siti ; Liong, The Houw ; Adiwijaya

  • Author_Institution
    Informatic Eng., Telkom Inst. of Technol., Bandung, Indonesia
  • fYear
    2012
  • fDate
    11-12 Sept. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Economic crisis that had happened at 1997-1998 in Indonesia has stimulated researchers to study it further by utilizing economic indicators. The economic indicators, GDP (Gross Domestic Product) and inflation per year from 1980-2011, will be tested using time series analysis and system dynamic optimized by genetic algorithm. This research have applied system dynamic in order to get characteristic value of prediction economic crisis in Indonesia with various conditions besides genetic algorithm (GA) is used to help the dynamic system in finding a coefficient of data historic optimization. The methods prior to predict consist of two phases, i.e. training and testing. The result shows 93%-99% accuracy for training and up to 90% for testing. It concludes that the prediction system is able to fit data in finding historical optimal without avoid error.
  • Keywords
    economic cycles; genetic algorithms; inflation (monetary); time series; GDP; Indonesia; data historic optimization; economic crisis prediction system; economic indicator; genetic algorithm; gross domestic product; inflation per year; system dynamic optimization; time series analysis; Accuracy; Biological system modeling; Economic indicators; Genetic algorithms; Testing; Time series analysis; GDP; genetic algorithm; inflation; system dynamic; testing; training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Engineering and Technology (ICSET), 2012 International Conference on
  • Conference_Location
    Bandung
  • Print_ISBN
    978-1-4673-2375-8
  • Type

    conf

  • DOI
    10.1109/ICSEngT.2012.6339339
  • Filename
    6339339