Drop Out Students Identification Using Knowledge Base

bit-Tech Pub Date : 2019-10-30 DOI:10.32877/bt.v2i1.102
Dara Kusumawati, Dini Faktasari
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Abstract

The purpose of this study is modeling for the initial identification of college dropout students. Samples were taken from drop out student data for the past 4 years. Information from this sample will be acquired as a knowledge base in system modeling. The research aims to provide a knowledge-based system approach using Dempster Shafer for the management of student drop outs at universities especially in Yogyakarta. The symptoms of DO students are obtained from knowledge about DO that appears on campus in Yogyakarta. The system output is in the form of 3 groups of classification namely initial potential DO, enough potential and once potential. The results of the study produced a system that could help university managers deal with drop-out problems early.
利用知识库识别辍学学生
本研究的目的是建立大学辍学学生的初步识别模型。样本取自过去4年的辍学学生数据。从这个样本中获取的信息将作为系统建模中的知识库。该研究的目的是提供一种基于知识的系统方法,使用Dempster Shafer来管理大学的学生退学,特别是在日惹。DO学生的症状是从日惹校园出现的DO知识中获得的。系统输出分为初始电位DO、足够电位和一次电位3组分类。这项研究的结果产生了一个系统,可以帮助大学管理者尽早处理退学问题。
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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