Clinical Decision Support System for Mapping of Blood Pressure and Heart Rate

Sri Sumarlinda (Universitas Duta Bangsa Surakarta)
Wiji Lestari (Universitas Duta Bangsa Surakarta)

Proceeding of International Conference Health, Science And Technology (ICOHETECH)
2021: Proceeding of the 2nd International Conference Health, Science And Technology (ICOHETECH)

Blood pressure has influence on cardiovascular diseases. This study aims to develope clinical decision support system (CDSS) model which non rule based system. The model eas improved using data mining function, especially clustering. K-Means algorithm was used to clustering 120 data and 4 attributes{ age, obesity, sistolic, diastolic and heart rate The clustering process used 500 epoches and 3 cluster. The result of clustering produced 3 cluster. Cluster 1 is higher risk, cluster 2 is medium risk and cluster 3 is normal or lower risk.