退学学生预测系统使用数据挖掘方法与CHAID算法

Dhila Franzely Dhimas Putra, Yogasetya Suhanda, Miri Susanti
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引用次数: 0

摘要

大学生活离不开学生面临的问题。这个问题是完成研究的障碍之一。学生辍学对高等教育机构是不利的,因为它会降低绩效指标,伤害学生自己。本研究的目的是通过对1992年至2019年ITB Swadharma的数据进行处理,并使用Chaid算法进行建模,利用数据挖掘技术建立一个大学生辍学预测系统,并通过tableau应用程序将结果可视化。研究结果显示,学习时间是影响辍学学生预测的主要因素,其卡方值为15,714,认证状态是影响辍学学生预测的主要因素,其卡方值为16,874,性别是影响辍学学生预测的主要因素,其卡方值为5.292。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SISTEM INFORMASI PREDIKSI MAHASISWA PUTUS KULIAH MENGGUNAKAN METODE DATA MINING DENGAN ALGORITMA CHAID
College life cannot be separated from problems faced by students. This problem is one of the obstacles in completing the study. Droped out students are detrimental to higher education institutions because it will reduce the performance index and harm the students themselves. The purpose of the research is to produce a prediction system for students who will drop out of college using data mining by processing data from ITB Swadharma for the period 1992 to 2019 and modeling using the Chaid algorithm, the results are visualized with the tableau application. The results of the study reveal the fact that the study time is the main factor that influences the prediction of dropout students with a chi-square value of 15,714, factor of accreditation status with a chi-square value of 16,874, gender is the factor with a chi-square value of 5.292.
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