研究计划分类系统信息工程的Ubhara泗水

W. Septiana, Eko Prasetyo, R. Purbaningtyas, Teddy Wishadi, Emanuel Suprihadi
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引用次数: 0

摘要

提高一所大学质量的一个指标是按时毕业的学生人数。但在泗水的巴扬卡拉大学,经常出现的问题是入学人数和毕业人数不平衡。因此,本研究采用社会研究1-4学期、学校出身、工作状态、早晚班状态、性别等变量对学生的学习时间进行分类。本研究旨在使用naïve贝叶斯方法对学生按时或迟到学习的时间长短进行分类。研究结果表明,该系统能够对每批实验中进行的训练数据和测试数据进行分类,最高准确率为59%,最低准确率为56%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study Program Classification System Informatics Engineering of Ubhara Surabaya
One indicator to improve the quality of a university is the number of students who graduate on time. But the problem that often occurs at Bhayangkara University in Surabaya is the number of students entering and the number of students graduating unbalanced. Therefore this research was made to classify the period of study of students by using variables in the form of social studies semester 1-4, school origin, work status, morning / evening class status, and sex. This study aims to classify the length of time a student studies on time or late using the naïve bayes method. The results of this study indicate that the system is able to classify training data and test data on experiments conducted in each batch, the highest accuracy results are 59% and the lowest accuracy results are 56%.
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