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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA
M. Hasyim Arrasyid
Universitas Budi Darma, Medan
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Clustering Penilaian Kinerja Guru Menggunakan Algoritma K-Means Donni Tambunan; M. Hasyim Arrasyid; Eferoni Ndruru
TIN: Terapan Informatika Nusantara Vol 3 No 2 (2022): July 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v3i2.3545

Abstract

Assessment of teacher quality is one of the important things that schools really need. Imelda Medan Private High School every year conducts a performance appraisal of teachers. However, there are still obstacles such as printing and distributing questionnaires which are considered less efficient, requiring a lot of money and effort. As well as not using a particular system or method in processing the results of the questionnaire into grades and graphs for monthly reports and determining the best teacher. The clustering technique is one technique for assessing a teacher's performance and the K-Means algorithm is one of the clustering technique algorithms. This technique is very suitable for use in this study, namely evaluating the performance of teachers at Imelda Medan Private High School. The result of this study is the application of data mining with the K-Means algorithm method which can assess a teacher's performance using the criteria that have been obtained at the data collection stage.
Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menerapkan Metode MAUT Muhammad Annur Al Fajar Nst; M. Hasyim Arrasyid; Eferoni Ndruru
TIN: Terapan Informatika Nusantara Vol 3 No 2 (2022): July 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v3i2.3639

Abstract

The selection of the best employee is the company's appreciation for the performance of its employees. This can motivate employees to be more motivated at work. To get the names of the best employees, a system is needed that performs the expected selection process and can produce objective and transparent information. In finding the best employees, the company does this by appointing without a reliable enough assessment. Therefore, a decision support system is needed in evaluating employee performance. This research uses the multi-attribute utility theory method. The data processed for this evaluation are 10 samples from CV Aurelia Weida Prima Medan. The evaluation is based on several criteria and weights given. There are 6 data criteria to assess employee performance, namely service (30% weight), integrity (20% weight), commitment (15% weight), discipline (20% weight), cooperation (13% weight), and employee performance (12% weight). From the calculation results, the employee who has the highest score is obtained. Therefore, the maximum value is obtained at A9 = 15.746, and the minimum value is obtained at A1 = 1.410. Will be considered for CV later. Aurelia Weida Prima Medan evaluates its employees over a while. It turns out that choosing the best employee performance helps CV. Aurelia Weida Prima Medan
Co-Authors Donni Tambunan Muhammad Annur Al Fajar Nst Ndruru, Eferoni