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    Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases

    199742_Ikasari 2014.pdf (2.026Mb)
    Access Status
    Open access
    Authors
    Ikasari, Novita
    Date
    2014
    Supervisor
    Dr Fedja Hadzic
    Dr Tom Cronje
    Type
    Thesis
    Award
    PhD
    
    Metadata
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    School
    School of Economics and Finance
    URI
    http://hdl.handle.net/20.500.11937/2619
    Collection
    • Curtin Theses
    Abstract

    This research is aimed at constructing an objective and accurate credit risk assessment method for Micro, Small and Medium Enterprises in Indonesia. Credit data of three sample banks is structured using eXtensible Markup Language and Database Structure Model for analysis purposes. Selected data mining techniques are applied to perform credit risk classification based on quantitative and text-based qualitative information. This fills the gap in previous studies where text-based qualitative information was excluded from the models.

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