Penerapan K-means Clustering untuk Pengukuran Kinerja Programmer di Software House - Alya Fitria; Taufik Ardiansyah Putra; Syahiduz Zaman (Jurnal Informatika dan Rekayasa Perangkat Lunak, 2024)
Performance evaluation of programmers plays a crucial role in maintaining efficiency within a software development company. This study proposes the implementation of K-means clustering as a method to measure and categorize programmer performance based on several criteria. The proposed approach involves assessing code quality, productivity, technical skills, team collaboration, and problem-solving abilities. By applying the K-means clustering method, programmers can be grouped into different performance clusters, allowing for the identification of high, moderate, and developmental performers. The K-means clustering method divides data into clusters related by calculating the distance between data points and cluster centers, and iterates until stable clusters are formed..