Penerapan Metode K-Means Untuk Evaluasi Kinerja Karyawan PT. PLN Unit Induk Distribusi Banten
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Aulia, Ahmad Dzaki
Wulandari, Dewi Arianti
Cipta W,, Max Teja Ajie
Wulandari, Dewi Arianti
Cipta W,, Max Teja Ajie
Subject
Teknik Informatika
Datestamp
2022-09-20 02:11:28
Abstract :
Large company data for State companies such as PT. PLN is something normal. HR Division of PT. PLN really needs to process this large number of employee data. An application that can support the HR division is needed to improve employee performance. In designing the grouping application, in this study using the K-Means Clustering method to classify employee performance. The results of the calculation of the status of the cluster obtained 169 employees thanks to good performance, 208 employees were categorized as good and 458 employees were categorized as poorly performing. The results of grouping talent received 473 employees in the very good category, 214 employees in the good category and 150 employees in the poor performance category. The grouping results received 620 employees categorized as very good, 27 employees categorized as good and 141 employees categorized as having poor performance.
Large company data for State companies such as PT. PLN is something normal. HR Division of PT. PLN really needs to process this large number of employee data. An application that can support the HR division is needed to improve employee performance. In designing the grouping application, in this study using the K-Means Clustering method to classify employee performance. The results of the calculation of the status of the cluster obtained 169 employees thanks to good performance, 208 employees were categorized as good and 458 employees were categorized as poorly performing. The results of grouping talent received 473 employees in the very good category, 214 employees in the good category and 150 employees in the poor performance category. The grouping results received 620 employees categorized as very good, 27 employees categorized as good and 141 employees categorized as having poor performance.
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