Application of Academic Potential Test for New Student Admission Using Fisher-Yates Shuffle Algorithm

Abdul Azis, Agung Triayudi, Endah Tri, Esti Handayani
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Abstract

The selection process of new students in educational institutions, such as in Sekolah Menengah Kejuruan (SMK) Wisata Indonesia which still uses conventional methods using paper, has several challenges. One of the main challenges is test cheating, where prospective students may try to manipulate their test results to increase their chances of being accepted. In addition, another challenge faced by SMK Wisata Indonesia is that when the number of prospective students who register is very large, managing answers and exam results can become more complicated. This research aims to design and build an Android-based Academic Potential Test application by applying the Fisher-Yates Shuffle algorithm to randomize the order of questions. This research also uses the RUP (rational Unified Process) system development technique which has several phases, namely the Inception phase, Elaboration phase, Construction phase and Transition phase. The validation testing carried out obtained overall valid results so that the application that has been designed is in accordance with user needs. Meanwhile, usability testing in the Academic Potential Test Application using the SEQ method resulted in an average Likert score for students of 6.63 with a user-friendliness percentage of around 94%. As for teachers, the Likert average score is 6.53 with a percentage of ease of use of around 93%. This shows that the Academic Potential Test Application that has been built is EASY TO USE
使用费舍尔-耶茨洗牌算法在新生录取中应用学术潜力测试
教育机构(如印度尼西亚维萨塔学校(SMK))在新生选拔过程中仍采用传统的纸质选拔方法,因此面临诸多挑战。其中一个主要挑战是考试作弊,即未来的学生可能会试图操纵他们的考试成绩,以增加被录取的机会。此外,SMK Wisata Indonesia 面临的另一个挑战是,当注册的准学生人数非常多时,答案和考试成绩的管理会变得更加复杂。本研究旨在设计和构建一个基于安卓系统的学术潜能测试应用程序,采用费舍尔-耶茨洗牌算法(Fisher-Yates Shuffle algorithm)随机调整试题顺序。本研究还采用了 RUP(合理统一过程)系统开发技术,该技术分为几个阶段,即初始阶段、阐述阶段、构建阶段和过渡阶段。所进行的验证测试获得了总体有效的结果,从而使所设计的应用程序符合用户需求。同时,使用 SEQ 方法对学术潜力测试应用程序进行的可用性测试结果显示,学生的平均 Likert 分数为 6.63,用户友好度约为 94%。教师的李克特平均得分为 6.53 分,易用性百分比约为 93%。由此可见,所开发的学业潜能测试应用程序是易于使用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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