Implementation of K-Means Algorithm to Group Age of Cardiovascular Disease Patients: Impelementasi Algoritma K-means untuk Mengelompokkan Usia Penderita Penyakit Kardiovaskular

Rahmi, Mulya Asy-syifa
Arum, Prizka Rismawati
Wahyu Utami, Tiani

Journal of Data Insights
Vol 3 No 1 (2025): Journal of Data Insights

Cardiovascular disease, including coronary heart disease, peripheral arteries and heart failure, is a serious disease that is the leading cause of death globally. Risk factors such as high blood pressure, dyslipidemia, smoking, diabetes, and obesity contribute to the development of this disease. This study aims to group cardiovascular disease sufferers based on age using the k-means clustering method with optimization of the k value using the elbow method. The data used comes from more than 35,000 preprocessed observations. The analysis results show that the optimal number of clusters is five. Data preprocessing succeeded in cleaning the data from missing values, and the elbow method helped determine the number of clusters that were relevant for age grouping of cardiovascular disease sufferers. The results of this grouping can be used for further analysis in efforts to prevent and manage cardiovascular disease.