Simulasi Perhitungan Analisis Cluster pada Kasus Penyakit Menular Menggunakan Bahasa Pemrograman Python

Aulia Wanda Puspitasari (Departemen Matematika, Fakultas MIPA, Universitas Padjadjaran)
Herlina Napitupulu (Departemen Matematika, Fakultas MIPA, Universitas Padjadjaran)
Nurul Gusriani (Departemen Matematika, Fakultas MIPA, Universitas Padjadjaran)

In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Vol 22 No 2 (2023): In Search

Increasing the prevention and control of infectious diseases is currently one of the 2020-2024 health development strategic goals set by the Ministry of Health. If it left unchecked, infectious diseases can become Kejadian Luar Biasa (KLB) which result in many deaths. To optimize the handling of infectious disease transmission, it is necessary to determine which groups are the priority. One of the grouping methods that can be used is cluster analysis. This study aims to find the best cluster based on the Cophenetic Correlation Coefficient (CPCC) and Pseudo-F values. The results showed that the average linkage method was the best method with a CPCC value closest to 1, that is 0.8513. The average linkage method divides districts/cities in West Java into five clusters based on the highest Pseudo-F value.