Komparasi Metode Clustering K-Means, Dbscan dan Hierarchical Untuk Analisis Penyakit Hepatitis C

Aditya Bachtiar (UIN Sunan Ampel Surabaya)
Nur Irvan Rizqi
Syahrul Mubarok

Journal Information System Development
Vol 8 No 1 (2023): Journal Information System Development

In recent years, a disease that is often avoided by humans is hepatitis. Hepatitis is a disease that spreads to the human liver which becomes inflamed so that the function of the liver is stagnant. With the sluggish function of the liver, it will affect other organs in humans and result in blood flow not reaching the liver so that blood pressure becomes abnormal and blood vessels rupture. This study uses the clustering method with datasets contained in the UCI Repository and then compares the three algorithms namely Hierarchical, K-Means, and DBSCAN which aims to find out which algorithm is the best of the three algorithms. the results of this study indicate that the algorithm Hierarchical is the best with a value of 0.7779 without using any scaler.