PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK PENGLOMPOKAN PASIEN BERDASARKAN DIAGNOSIS DI RUMAH SAKIT AL-RASYID PALEMBANG - Nurcholis; Dafid (PT. Hasba Edukasi Mandiri, 2026)
The advancement of information technology has compelled hospitals to not only provide accurate and timely medical services but also to manage patient data effectively. Al Rasyid Islamic Hospital Palembang faces challenges in allocating medical personnel efficiently due to underutilization of medical record data. This study aims to develop a patient clustering system based on diagnoses using the K-Means Clustering algorithm. Utilizing outpatient medical record data from 2022 to 2024, the system groups patients based on diagnosis, age, and gender. The development process follows the CRISP-DM methodology, which includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment stages. Clustering results are presented through a web-based dashboard to support hospital management in medical personnel allocation planning. This research is expected to improve the efficiency of healthcare services through data-driven analysis.