基于简单相加加权(SAW)方法的贷款资格决策支持系统

M Reza Tri Kurnia, Eka Praja Wiyata Mandala, Radius Prawiro
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引用次数: 0

摘要

索洛克市巴克蒂·胡萨达雇员合作社是合作社形式的非银行金融机构,以成员储蓄形式的抵押品满足其成员的贷款服务需求。本研究的目的是使Bakti Husada合作社更容易确定向借款人提供贷款的适宜性,并使用简单加法加权(SAW)方法创建一个决策系统,该系统能够帮助Bakti Husada合作社确定向借款人提供贷款的适宜性。数据收集方法是通过直接观察和对索洛克市Bakti Husada合作社员工的访谈进行的。所获得的结果对于根据甄选中确定的标准,在索洛克市Bakti Husada合作社作出贷款资格的决策是有效的。这一结果得到了证明。通过使用该系统,申请贷款的成员可以根据设定的标准和权重得到一个分数,从中可以看出是否有不符合成员申请贷款的标准要求的标准,以便成员可以改进贷款要求,从而使贷款申请被合作社接受。Gusnelawati使用SAW法确定合作社贷款可行性的计算结果为0.9625,在该决策中排名第一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision Support System for Loan Eligibility using the Simple Additive Weighting (SAW) Method
The Solok City Bakti Husada Employees Cooperative is a non-bank financial institution in the form of a cooperative that serves the needs of its members in lending services with collateral in the form of member savings. The aim of this research is to make it easier for the Bakti Husada Cooperative to determine the suitability of loans to borrowers and to create a Decision Making System using the Simple Additive Weighting (SAW) method which is able to assist the Bakti Husada Cooperative in determining the suitability of loans to borrowers. The data collection method was carried out by direct observation and interviews with employees from the Bakti Husada Cooperative, Solok City. The results obtained are effective in making decisions about loan eligibility at the Bakti Husada Cooperative in Solok City in accordance with the criteria that have been determined in the selection. This result is proven. By using this system, members who apply for a loan get a score that is in accordance with the criteria and weights that have been set and from there it can be seen if there are criteria that are not in accordance with the standard requirements of the member's application for a loan so that members can improve the loan requirements so that Loan applications are accepted by the cooperative. Gusnelawati obtained the calculation results using the SAW method to determine the feasibility of providing loans to cooperatives with a value of 0.9625 and was the 1st Best in making this decision.
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