Implementation of the Greedy Algorithm for Determining KKN (Kuliah Kerja Nyata) Grouping in the Development of the Kuningan University Kkn Online System Service Based on Mobile Applications

Rio Priantama, Aji Permana, F. Nugraha, Dudi Rahmadi
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Abstract

. KKN (Kuliah Kerja Nyata) is an academic activity in the form of community service programs carried out by students in an interdisciplinary and cross-sectoral manner. Those who have been registered as KKN (Kuliah Kerja Nyata) participants will be divided into several groups where each group is determined based on the criteria of gender and majors. The purpose of this study is to build a system for determining the KKN (Civil Work) group automatically based on gender and majors evenly and optimally. To build a system for determining the KKN (Kuliah Kerja Nyata) class, a greedy algorithm is used. The application of the greedy algorithm is done by dividing the composition of participants into one group based on gender criteria. This system uses PHP as the programming language, Apache as the web server and MYSQL as the database. The results of this study indicate that the Greedy Algorithm can be implemented in an optimal and ideal system for determining groups of KKN participants.
基于移动应用的库宁安大学KKN在线系统服务开发中确定KKN (Kuliah Kerja Nyata)分组的贪心算法的实现
。KKN (Kuliah Kerja Nyata)是一项由学生以跨学科和跨部门的方式开展的社区服务项目形式的学术活动。注册为KKN (Kuliah Kerja Nyata)参与者的人将被分成几个小组,每个小组根据性别和专业的标准确定。本研究的目的是建立一个基于性别和专业的KKN(土建工程)群体的平均和最优自动确定系统。为了建立一个确定KKN (Kuliah Kerja Nyata)类的系统,使用了贪婪算法。贪心算法的应用是根据性别标准将参与者的组成分成一组。本系统采用PHP作为编程语言,Apache作为web服务器,MYSQL作为数据库。研究结果表明,贪心算法可以在确定KKN参与者群体的最优理想系统中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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