Decision support system for loan based using data mining

  • Unique Paper ID: 145705
  • PageNo: 58-60
  • Abstract:
  • A Decision Support Systems (DSS) is a particular type of computerized information system that support business and organizational decision making activities. on the other hand, Data Mining (DM) expand the potentials for decision support by finding styles and connections hidden in the data and in this way enabling an inductive way to deal with data analysis. Data is analyzed through a mechanized process, known as Knowledge Discovery in data mining techniques. Data mining can be characterized as a process of browsing and analysis for large amounts of data with a particular focus on discovering significantly important patterns and rules. Data mining helps discovering knowledge from raw, not equipped data. Utilizing data mining techniques permits extracting knowledge from data mart, data warehouse and, specifically cases, even from operational databases. In this paper a methodology is introduced to integrate the DSS with DM for loans to the Real Estate developments fund (REDF) Customers. It causes to cooperative interaction of DSS, through getting more options to analysis, utilizing expert's data, and improving assessment process. So I will talk about the function of data mining to simplify decision support, the utilization of data mining methods in decision support systems, talking about applied approaches and present a data mining decision support system called DMDSS – (Data Mining Decision Support System). We also present some obtained results and plans for future development.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{145705,
        author = {P.Yashwanth and G.Anjanbabu},
        title = { Decision support system for loan based using  data mining },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {11},
        pages = {58-60},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145705},
        abstract = {A Decision Support Systems (DSS) is a particular type of computerized information system that support business and organizational decision making activities. on the other hand, Data Mining (DM) expand the potentials for decision support by finding styles and connections hidden in the data and in this way enabling an inductive way to deal with data analysis. Data is analyzed through a mechanized process, known as Knowledge Discovery in data mining techniques. Data mining can be characterized as a process of browsing and analysis for large amounts of data with a particular focus on discovering significantly important patterns and rules. Data mining helps discovering knowledge from raw, not equipped data. Utilizing data mining techniques permits extracting knowledge from data mart, data warehouse and, specifically cases, even from operational databases.  In this paper a methodology is introduced to integrate the DSS with DM for loans to the Real Estate developments fund (REDF) Customers. It causes to cooperative interaction of DSS, through getting more options to analysis, utilizing expert's data, and improving assessment process. So I will talk about the function of data mining to simplify decision support, the utilization of data mining methods in decision support systems, talking about applied approaches and present a data mining decision support system called DMDSS – (Data Mining Decision Support System). We also present some obtained results and plans for future development.},
        keywords = {},
        month = {},
        }

Cite This Article

P.Yashwanth, , & G.Anjanbabu, (). Decision support system for loan based using data mining . International Journal of Innovative Research in Technology (IJIRT), 4(11), 58–60.

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