Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases
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 mini...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
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Curtin University
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/2619 |
| _version_ | 1848744003784146944 |
|---|---|
| author | Ikasari, Novita |
| author_facet | Ikasari, Novita |
| author_sort | Ikasari, Novita |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T05:54:33Z |
| format | Thesis |
| id | curtin-20.500.11937-2619 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:54:33Z |
| publishDate | 2014 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-26192017-02-20T06:38:35Z Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases Ikasari, Novita 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. 2014 Thesis http://hdl.handle.net/20.500.11937/2619 en Curtin University fulltext |
| spellingShingle | Ikasari, Novita Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases |
| title | Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases |
| title_full | Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases |
| title_fullStr | Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases |
| title_full_unstemmed | Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases |
| title_short | Credit decision support methodology for Micro, Small and Medium Enterprises (MSMEs) : Indonesian cases |
| title_sort | credit decision support methodology for micro, small and medium enterprises (msmes) : indonesian cases |
| url | http://hdl.handle.net/20.500.11937/2619 |