Analisa Data Penerimaan Siswa Pada Perguruan Tinggi melalui Jalur SNMPTN menggunakan Algoritma Fuzzy C-Means (Studi Kasus : SMAN 5 Kota Bengkulu)

Aan Herwansah
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Abstract

SMA Negeri 5 Bengkulu City is one of State Senior High Schools in Bengkulu City that has been accredited A with a total of 58 educators and 23 administrative staff and employees. In addition, SMA Negeri 5 Bengkulu City has also won many achievements both in academics (graduates of SMA N 5 Bengkulu City are accepted at the best universities in Indonesia through test and non-test pathways) as well as in the fields of science (Olympics), Sports, IMTAQ and the arts for the provincial and national levels. Application of student admissions data in higher education through SNMPTN using Fuzzy C-Means Algorithm at SMA N 5 Bengkulu City is an application that can help analyze data grouping based on student admission data into 3 groups. Data Analysis of Student Admissions in higher education through SNMPTN was made using the Visual Basic.Net programming language and SQL Server 2008 database by applying the Fuzzy C-Means algorithm. This application is able to provide information on the results of the analysis of student admissions at Higher Education through SNMPTN. The more data on student admissions in Higher Education, the more accurate the grouping results. Based on the results of the tests that have been carried out, the Application of Student Admission Data in Higher Education through SNMPTN can provide information on the results of data grouping divided into 3 groups, namely high, medium and low
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通过SNMPTN路径分析学生入学数据,使用模糊c -手段算法(案例研究:
SMA Negeri 5 Bengkulu City是Bengkulu City的一所获得A级认证的州立高中,共有58名教育工作者和23名行政人员和员工。此外,SMA Negeri 5 Bengkulu市在学术(SMA n5 Bengkulu市的毕业生通过考试和非考试途径被印度尼西亚最好的大学录取)以及科学(奥林匹克),体育,IMTAQ和省和国家级艺术领域也取得了许多成就。利用模糊c均值算法在smn5 Bengkulu市通过SNMPTN应用高等教育学生入学数据是一个可以帮助分析基于学生入学数据分组为3组的应用程序。利用Visual Basic对SNMPTN在高校招生中的数据进行了分析。Net编程语言和SQL Server 2008数据库,采用模糊C-Means算法。该应用程序能够通过SNMPTN提供有关高等教育学生入学分析结果的信息。高等教育录取学生的数据越多,分组结果就越准确。基于已经进行的测试结果,通过SNMPTN实现的高等学校学生录取数据的应用可以提供数据分组结果的信息,分为高、中、低三组
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