首页    期刊浏览 2024年11月08日 星期五
登录注册

文章基本信息

  • 标题:Predicted Student Study Period with C4.5 Data Mining Algorithm
  • 本地全文:下载
  • 作者:Agus Supriyanto ; Dwi Maryono ; Febri Liantoni
  • 期刊名称:IJIE (Indonesian Journal of Informatics Education)
  • 电子版ISSN:2549-0389
  • 出版年度:2021
  • 卷号:4
  • 期号:2
  • 页码:94-100
  • DOI:10.20961/ijie.v4i2.46265
  • 语种:English
  • 出版社:Universitas Sebelas Maret
  • 摘要:Data of alumni from 2012 to 2015 found that the average percentage of students graduating on time was 22%. The comparison between the number of students who graduate on time and new students who enter each year is not comparable, therefore a study is needed to find out the factors that affect student graduation and to prediction of the graduation period of the student through data mining research using the C4.5 algorithm. The data tested was student alumni data from 2012 to 2015. The instruments studied include study period, academic year, GPA, corner focus, gender, intensity of work during college, type of thesis, intensity of campus internal organization, intensity of external organization of campus, UKT group, scholarship status, pre-college education, hobby intensity, intensity of game play, academic competition participation status, non-academic competition participation status, and availability of facilities and infrastructure. The best test results using percentage-split 75% obtained 83.33% accuracy as well as the rules contained in the decision tree.
国家哲学社会科学文献中心版权所有