Comparative Analysis of Prediction Results of Decision Support Systems Simple Additive Weighting Method with Preference Selection Index in Determining Scholarship Recipients

None Medi Hermanto Tinambunan, None Djubir R.E. Kembuan, None Vivi Peggie Rantung, None Alfiansyah Hasibuan
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Abstract

Educational Assistance needs to be a concern because currently the majority of students have the potential and ability but are constrained financially so this needs to be taken seriously by the government, currently, the government through the Ministry of Education has been trying to provide financial assistance in the form of scholarships including achievement improvement scholarships academic. Currently, to get a scholarship, each university certainly gets a limited quota. This is done to provide equal distribution of educational assistance, due to the large difference between the quota obtained and students who need assistance, so it is necessary to provide eligibility selection for students who are entitled to get scholarships. This study took sample data from the 2023 even semester scholarship list at Manado State University, especially in the Informatics Engineering Study Program, then normalized the data to use the SAW and PSI methods. After normalization, calculations were carried out using the SAW and PSI methods. predictions from the two methods will then be tested for the level of accuracy using the confusion matrix method. The result is that the SAW method has an accuracy rate of 98.13% and then the PSI accuracy rate is 97.24% based on the results of the prediction accuracy, the SAW method has a higher accuracy rate than PSI.
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决策支持系统简单加性加权法与偏好选择指数预测结果的比较分析
教育援助需要引起人们的关注,因为目前大多数学生都有潜力和能力,但经济上受到限制,所以这需要政府认真对待,目前,政府通过教育部一直试图以奖学金的形式提供经济援助,包括学术成就提高奖学金。目前,为了获得奖学金,每所大学都有一定的配额。这样做是为了公平分配教育援助,由于获得的配额和需要援助的学生之间存在很大差异,因此有必要为有资格获得奖学金的学生提供资格选择。本研究从万纳多州立大学2023年偶数学期奖学金名单中获取样本数据,特别是在信息工程研究项目中,然后使用SAW和PSI方法对数据进行规范化。归一化后,使用SAW和PSI方法进行计算。然后将使用混淆矩阵方法测试两种方法的预测的准确性水平。结果表明,SAW法的预测准确率为98.13%,PSI法的预测准确率为97.24%,SAW法的预测准确率高于PSI法。
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