Employee Performance Segmentation In The Public Housing Service And Payakumbuh City Residential Area With Using The K-Means Clustering Model

Edvidel Arda (Magister Manajemen, Institut Teknologi dan Bisnis Haji Agus Salim Bukittinggi, Sumatera Barat)
Arif Aulia (Magister Manajemen Institut Teknologi dan Bisnis Haji Agus Salim, Bukittinggi)
Opel Saputra (Magister Manajemen Institut Teknologi dan Bisnis Haji Agus Salim, Bukittinggi)
Jerry Heikal (Magister Manajemen Institut Teknologi Haji Agus Salim, Bukittinggi, Indonesia)

JEBD
Vol. 1 No. 3 (2024): Januari - Maret

Effective employee performance management is one of the key factors in ensuring that the Department of Housing and Settlement Areas in Payakumbuh City operates efficiently and can respond to the evolving urban challenges. However, in a complex organization like this department, understanding employee performance and identifying areas that need improvement can be a very complex task. In this context, employee performance segmentation techniques, such as the use of K-means Clustering models, can be significantly helpful. This model allows us to group employees based on their performance characteristics, which, in turn, can be used to identify performance trends and issues that may exist. In this study, data processing is conducted using the K-means clustering method, which divides the data into 3 (three) clusters. The sample used in this research consists of 53 samples, comprising employees in the Department of Housing and Settlement Areas in Payakumbuh City, resulting in Cluster I classified as high cluster, Cluster II classified as low cluster, and Cluster III classified as a medium cluster.