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首页> 外文期刊>International Journal of Information Technology & Decision Making >Novel Multiperspective Hiring Framework for the Selection of Software Programmer Applicants Based on AHP and Group TOPSIS Techniques
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Novel Multiperspective Hiring Framework for the Selection of Software Programmer Applicants Based on AHP and Group TOPSIS Techniques

机译:基于AHP和Group Topsis技术的软件程序员申请人选择的新型多重招聘框架

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The selection of software programmer applicants based on multiperspective evaluation criteria (grade point average (GPA) and soft skills of the applicants) is needed instead of an interview because an interview does not necessarily lead to hiring the best candidate amongst the applicants. The selection of a suitable software programmer is considered a challenging task owing to the following factors: (1) data variation, (2) multiple evaluation criteria and (3) criterion importance. A general framework for the selection of the best software programmer applicants is not available in the existing literature. The present study aims to propose a novel multiperspective hiring framework based on multicriteria analysis to select the best software programmer amongst several applicants. A decision matrix (DM) is constructed for the selection of the best programmer applicants according to multiple criteria, namely, structured programming, object-oriented programming, data structure, database system and courseware engineering. Each criterion includes two parameters, namely, GPA and soft skills, and these criteria cross over with programmer applicants as alternatives. The standard and expert opinion of the Software Engineering Body of Knowledge is used to distribute the criteria in the DM. The two commonly used techniques of multicriteria decision-making are analytic hierarchy process (AHP) for weighing the criteria and technique for order performance by similarity to ideal solution (TOPSIS) for ranking the alternatives (programmer applicants). The data used in this study include 60 software engineering students who graduated in 2016 from Universiti Pendidikan Sultan Idris. Results show that integrating multilayer analytic hierarchy process (MLAHP) and group TOPSIS are effective for solving applicant selection problems. Group TOPSIS uses different contexts - internal and external aggregation - and indicates similar results. Objective validation is used for the ranking of the results, which are equally divided into four parts. Furthermore, the applicants are systematically ranked. This study benefits application software, system software and computer programming tool companies by providing a method that improves software quality whilst reducing time and cost in the selection process.
机译:需要基于多次值评估标准的软件程序员申请人(申请人的等级平均值(GPA)和软技能)而不是面试,因为面试并不一定导致申请人中最好的候选人。由于以下因素:(1)数据变化,(2)多评价标准和(3)标准重要性,选择合适的软件程序员的选择被认为是一个具有挑战性的任务在现有的文献中没有提供选择最佳软件程序员申请人的一般框架。本研究旨在提出一种基于多准则分析的新型多射目招聘框架,以在若干申请人中选择最佳的软件程序员。根据多标准,即结构化编程,面向对象编程,数据结构,数据库系统和课件工程,构建了决策矩阵(DM)以选择最佳的程序员申请人。每个标准包括两个参数,即GPA和软技能,以及这些标准用程序员申请人作为替代方案交叉。软件工程知识体的标准和专家意见用于分配DM中的标准。多种机构决策的两个常用技术是分析层次处理(AHP),用于称重通过相似性与用于排名替代品的理想解决方案(TOPSIS)的订单性能的标准和技术。本研究中使用的数据包括60名软件工程学生,他们于2016年毕业于苏丹·伊朗斯·伊朗斯结果表明,集成多层分析层次处理(MLAHP)和Group Topsis对申请人选择问题有效。 Group Topsis使用不同的上下文 - 内部和外部聚合 - 表示类似的结果。客观验证用于排名结果,其等于四个部分。此外,申请人系统地排名。本研究利用应用软件,系统软件和计算机编程工具公司通过提供一种提高软件质量的方法,同时减少选择过程中的时间和成本。

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