Fuzzy C-Means Clustering Algorithm For Grouping Health Care Centers On Diarrhea Disease

(1) * Ahmad Chusyairi Mail (Universitas Bina Insani, Indonesia)
(2) Pelsri Ramadar Noor Saputra Mail (STIKOM PGRI Banyuwangi, Indonesia)
(3) Efendi Zaenudin Mail (Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan, Province of China)
*corresponding author


In Indonesia, public health services at the city or district level are carried out by regional public hospitals or “puskesmas” (health care centers), especially in Banyuwangi regency, East Java, Indonesia that has 45 health care centers spread throughout the villages. This research focused on the deaths of babies caused by diarrhea diseases, which are the second leading cause of death among children younger than 5 years globally. All of the health care centers need to be divided into 3 groups to find out which health care centers have the least, most moderate, and many diarrhea sufferers. Fuzzy C-Means algorithm is used to overcome this problem. The result from this research shown that 2 health care centers have the smallest member of diarrhea sufferers, 14 health care centers have a medium member of diarrhea sufferers, and the rest have a large number of diarrhea sufferers. From the result of this study, it can be a reference for the health department center in dealing with diarrheal diseases, accordingly, the infant mortality rate due to diarrheal diseases can be lowered to health care centers that have high diarrhea sufferers.


Clustering Algorithm; Diarrhea Disease; Fuzzy C-Means; Health Care Center




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