Analisis Klaster Data Pasien Diabetes untuk Identifikasi Pola dan Karakteristik Pasien - Ananda Elang Satriatama; Ari Prasetyo Wibowo; I Gusti Ngurah Arnold; Reyhan Bayu Pratama; Tegar Alwinata Masyhuda; Yohannes Alexander Agusti; Endah Purwanti; Indah Werdiningsih (Prodi Sistem Informasi Universitas Dharma Andalas, 2023)
Diabetes is a significant health problem in Indonesia and the world. To understand the patterns and characteristics of diabetic patients, research was conducted by clustering the data of diabetic patients using the K-Means algorithm. The results of the analysis showed that there were two clusters, with cluster 1 consisting of 755 female patients aged 20-80 years and cluster 2 consisting of 404 male patients aged 40-90 years. The diagnosis of Non-insulin-dependent diabetes mellitus was the most common diagnosis in both clusters, followed by Rheumatoid arthritis in cluster 1 and Respiratory tuberculosis in cluster 2. BMI results in the