学生毕业时间预测决策支持系统仪表板的分析与设计

S. Wibowo, R. Andreswari, M. A. Hasibuan
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引用次数: 8

摘要

信息系统是电信大学现有的研究项目之一,自2008年成立以来,已经培养了许多毕业生。然而,并不是所有的毕业生都能在四年的正常学习中顺利完成学业。毕业生准时毕业的比例在目标和学习计划的实现之间有所下降。从2014/2015学年到2016/2017学年,每年减少约1%,这对学习项目的可信度和存在性造成了问题,也对学术策划者造成了问题,这些问题可能会对学习项目审核时的认证评估过程产生影响。为了提高学生的按时毕业率,学习项目可以做的一项努力是通过制定决策支持系统仪表板,如果有学生预计不能按时毕业,该仪表板会向讲师或学习项目负责人发出预警。通过使用C4.5算法进行数据分析,通过查看学生毕业时间的原因和pureshare方法论来执行仪表板开发方法。本研究的结果是一个决策支持系统仪表板的原型,因为在决策过程中缺乏分析,仪表板只显示信息和临时预测。本研究使用的数据模型是使用C4.5算法对处理过的数据进行标注,使用Pentaho data Integration对数据进行清洗处理的数据进行标注。这个原型有望被用作一个参考基础,以支持学术规划人员,以便使这个应用程序使用实时数据运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and Design of Decision Support System Dashboard for Predicting Student Graduation Time
Information Systems is one of the existing study program at Telkom University that has produced many graduates since it was established in 2008. However, not all graduates produced successfully completed the study period during the four years of normal study. The percentage of graduates on time has some decline between the target and the achievement of the study program. From academic year 2014/2015 to 2016/2017 decrease annually about 1% every year, which is it becomes problems for the credibility and existence of study program and also for academic planners who may have an impact on accreditation assessment process of the study program when it is audited. One of the efforts that can be done by the study program to increase the students on time graduation rate is by making decision support system dashboard that giving early warning to the lecturer or the head of the study program if there are students who are predicted not to graduate on time. By using the C4.5 algorithm to perform the data analysis by looking at the causes of student’s graduation time and pureshare methodology to perform dashboard development method. The result of this study is a prototype of decision support system dashboard, because there are lack of analysis in decision making and the dashboard only showing information and temporary prediction. The data model that used on this research is labeling data that has been processed using C4.5 algorithm and data that has been through data cleansing process using Pentaho Data Integration. This prototype is expected to be used as a reference base to support academic planners in order to make this application run with real time data.
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