Proceedings of the 2nd Universitas Kuningan International Conference on System, Engineering, and Technology, UNISET 2021, 2 December 2021, Kuningan, West Java, Indonesia

Research Article

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

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  • @INPROCEEDINGS{10.4108/eai.2-12-2021.2320256,
        author={Rio  Priantama and Aji  Permana and Fitra  Nugraha and Dudi  Rahmadi},
        title={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},
        proceedings={Proceedings of the 2nd Universitas Kuningan International Conference on System, Engineering, and Technology, UNISET 2021, 2 December 2021, Kuningan, West Java, Indonesia},
        publisher={EAI},
        proceedings_a={UNISET},
        year={2022},
        month={8},
        keywords={greedy algorithm; apache web server; kuliah kerja nyata},
        doi={10.4108/eai.2-12-2021.2320256}
    }
    
  • Rio Priantama
    Aji Permana
    Fitra Nugraha
    Dudi Rahmadi
    Year: 2022
    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
    UNISET
    EAI
    DOI: 10.4108/eai.2-12-2021.2320256
Rio Priantama1,*, Aji Permana1, Fitra Nugraha1, Dudi Rahmadi1
  • 1: Kuningan University, Kuningan, Indonesia
*Contact email: rio.priantama@uniku.ac.id

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.