APPLICATION OF THE K-MEANS CLUSTERING METHOD FOR PERFORMANCE ASSESSMENT BASED ON EDUCATOR COMPETENCE

Paul Erikson, Bobby Rahman Angkat, Eliza Christovel Yosua, Mutiara Sembiring, Marlince Nababan
{"title":"APPLICATION OF THE K-MEANS CLUSTERING METHOD FOR PERFORMANCE ASSESSMENT BASED ON EDUCATOR COMPETENCE","authors":"Paul Erikson, Bobby Rahman Angkat, Eliza Christovel Yosua, Mutiara Sembiring, Marlince Nababan","doi":"10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3869","DOIUrl":null,"url":null,"abstract":"Performance appraisal is one thing to respect someone while working in an institution, one of which is a private higher education institution. To respect the performance of resources, there needs to be a value assigned to someone. Assessments carried out for one semester need to be reviewed again because during filling in the student assessments do not fill in according to their understanding so that a review needs to be carried out again. The assessment was carried out using the K-Means method by applying the concept of the centroid value. There are 4 (four) variables used, namely pedagogic competence, personal competence, social and professional competence with a value of K = 3. The maximum number of observations for cluster 3 is 368 while the value of Distances Between Cluster Centroids shows 2 suitable clusters, namely cluster 1 and cluster 2, which is 1.7020. The author gives suggestions to remove outlier data before entering the data to be trained into the algorithm to improve visualization if the dataset is large. Key Word: Performance Appraisal, Data Mining, K-Means","PeriodicalId":499639,"journal":{"name":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jusikom : Jurnal Sistem Informasi Ilmu Komputer","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.3869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Performance appraisal is one thing to respect someone while working in an institution, one of which is a private higher education institution. To respect the performance of resources, there needs to be a value assigned to someone. Assessments carried out for one semester need to be reviewed again because during filling in the student assessments do not fill in according to their understanding so that a review needs to be carried out again. The assessment was carried out using the K-Means method by applying the concept of the centroid value. There are 4 (four) variables used, namely pedagogic competence, personal competence, social and professional competence with a value of K = 3. The maximum number of observations for cluster 3 is 368 while the value of Distances Between Cluster Centroids shows 2 suitable clusters, namely cluster 1 and cluster 2, which is 1.7020. The author gives suggestions to remove outlier data before entering the data to be trained into the algorithm to improve visualization if the dataset is large. Key Word: Performance Appraisal, Data Mining, K-Means
k -均值聚类方法在教师能力绩效评估中的应用
绩效评估是在一个机构工作时尊重一个人的一件事,其中一个是私立高等教育机构。为了尊重资源的性能,需要给每个人分配一个价值。一个学期的评估需要重新审查,因为在填写学生评估时没有根据他们的理解填写,所以需要重新进行审查。采用K-Means方法,应用质心值的概念进行评价。使用了4(4)个变量,即教学能力、个人能力、社会能力和专业能力,其值K = 3。聚类3的最大观测数为368,而聚类质心之间的距离值为1.7020,显示出2个合适的聚类,即聚类1和聚类2。在数据集较大的情况下,作者给出了在将待训练数据输入算法之前去除离群数据的建议,以提高可视化。关键词:绩效评估,数据挖掘,k均值
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信