E-Recruitment BEM PSDKU Polinema Di Kota Kediri (Rekomendasi Pemilihan Kementrian Menggunakan Metode K-Nearest Neighbor)

Authors

  • Fadelis Sukya Politeknik Negeri Malang
  • Isna Uswatun K Politeknik Negeri Malang
  • Muhamad Efendi M Politeknik Negeri Malang

DOI:

https://doi.org/10.33795/jim.v14i1.356

Keywords:

Sistem Infromasi, E-Recruitment, BEM, Sistem Pendukung Keputusan, K-Nearest Neighbor

Abstract

Open Recruitment is an activity that must be carried out every year by BEM PSDKU to recruit new members. So far, these activities are still carried out manually by collecting registration files and registration forms in hardfile form to the committee. So that the committee must check the participant's files one by one and it will take a long time. In addition, the risk of losing files is also very possible, even though registration data is important data for the implementation of the next selection. Another problem is that participants are often confused and hesitant to decide which ministry to choose when registering as a new member of the BEM. Usually to overcome this problem participants only consult directly with existing BEM members so that they get a recommendation for a ministry position that suits their interests or seek information independently on BEM social media.
Therefore, it is necessary to develop an online Recruitment system for the Ministry's Recommendation section using the website-based K-Nearest Neighbor Method. The system is designed and implemented using PHP, MySQL, HTML, CSS, JavaScript, and Boostrap. This system has also been tested by several users and the result is that each user can process form data and participant registration files more easily and quickly. In addition, participants can also use the available decision support system to obtain recommendations from the ministry as a provision to register at the BEM.

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Published

2022-07-27

How to Cite

Fadelis Sukya, Uswatun K, I., & Efendi M, M. (2022). E-Recruitment BEM PSDKU Polinema Di Kota Kediri (Rekomendasi Pemilihan Kementrian Menggunakan Metode K-Nearest Neighbor). Jurnal Informatika Dan Multimedia, 14(1), 12–17. https://doi.org/10.33795/jim.v14i1.356