KLASIFIKASI TINGKAT KEPUASAN MAHASISWA TERHADAP FASILITAS PADA FTIK UNIVERSITAS DHARMAWANGSA MEDAN DENGAN ALGORITMA NAIVE BAYES

Medi Hermanto Tinambunan, Alfiansyah Hasibuan, S. Wahyuni, A. Wibowo
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Abstract

ABSTRACT Facilities are a support for the implementation of a process in a business in this case the Dharmawangsa University campus, by increasing the level of student satisfaction with the facilities available, student comfort in learning will be achieved. This study used questionnaire data on 70 respondents who were students of Dharmawangsa University. Previously, the questionnaire consisted of 42 questions. After being tested for validity and reliability, 20 questions were obtained. Then from the results of the questionnaire data, a classification of student satisfaction levels will be carried out using one of the algorithms in data mining, namely Naive Bayes. The results obtained by using the rapid miner application with 50 training data and 19 data testing data, the results obtained are a classification accuracy of 73.68% with a recall value of 83.33% and a precision of 83.33%, then there are 9 attributes that have a value dissatisfaction is higher than the satisfaction score given by respondents, this can be a concern of the leadership to improve these facilities so as to increase the level of satisfaction with the facilities provided by Dharmawangsa University.Keywords: Student Satisfaction, Data Mining, Naive Bayes
学生满意度等级的学生满意度与NAIVE BAYES算法
设施是在商业过程中实施的支持,在这个案例中,Dharmawangsa大学校园,通过提高学生对现有设施的满意度,学生在学习中的舒适度将得到实现。本研究采用问卷调查资料,调查对象为达玛旺萨大学70名学生。以前,问卷由42个问题组成。经过效度和信度检验,得到20个问题。然后根据问卷数据的结果,使用数据挖掘中的一种算法,即朴素贝叶斯,对学生满意度进行分类。使用快速挖掘器应用50个训练数据和19个数据测试数据得到的结果是,分类准确率为73.68%,召回率为83.33%,精度为83.33%,其中有9个属性的值不满意高于被调查者给出的满意度得分;这可能是领导层关注的问题,以改善这些设施,以提高对达玛旺萨大学提供的设施的满意度。关键词:学生满意度,数据挖掘,朴素贝叶斯
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