Penerapan Algoritma K-Medoids Dalam Pengelompokan Imunisasi Lanjutan Pada Anak Usia 2 Tahun

Abstract

Immunization is a process to make someone immune or immune to a disease. This process is carried out by administering a vaccine that stimulates the immune system to be immune to the disease. Immunization in children needs to be done because the immune system that has not been good causes various viruses and bacteria that can interfere with children's health. Advanced immunization is a continuation of basic immunization, at this stage of immunization serves as a reinforcement of endurance in children aged 2 years. This study aims to create a grouping model using the K-Medoids algorithm. K-Medoids algorithm or also known as PAM (Partitioning Around Medoids) uses the clustering partition method to group a group of n objects into a number of k clusters. The data in this study were sourced from the Ministry of Health from 2017 to 2019. The grouping was based on the number of recipients of the DPT-HB-HiB and Measles / MR vaccine from 34 Provinces in Indonesia. From the research results obtained 3 clusters with members, namely: cluster 1 contains 1 province, cluster 2 contains 18 provinces, cluster 3 contains 15 provinces. It is hoped that this research can be a reference to the Government in improving services in the immunization program, especially in advanced immunizations so as to ensure the health level of children in Indonesia.