Pengklasterisasian Data Penyakit Hipertensi dengan Menggunakan Metode K-Means

The increasing number and variety of diseases suffered by the community due to lifestyle changes that are influenced progress times. Periodic disease data collection will increase accumulation data. This is often an error in search process so it takes a long time study focuses on hypertension aims cluster method used this CRISP-DM with business understanding process, understanding, preparation, modeling, evaluation deployment. algorithm clustering K-Means algorithm. results resulted 2 clusters, namely 0 Normal 1 Hypertension. can provide information about Hypertension