Fuzzy C-means Cluster Pattern Analysis and Ward Model Mapping in Viewing the Growth of Infectious and Non-Infectious Diseases Children in North Aceh
Mauliza Mauliza, Mutammimul Ula, Ilham Sahputra, Rosya Afdelina · 2023
The problems and challenges for the government in seeing disease growth trend patterns are very important. This research focuses on infectious diseases, namely Dengue Hemorrhagic Fever (DHF), while non-communicable illnesses focus on epilepsy and thalassemia in 2023-2024. The priority in this research is that the Health Service can take action to prevent disease distribution patterns that are seen based on the results of identifying patterns and trends using the fuzzy c-means model and mapping for each region. The research methodology includes collecting patient data, inputted by recorded medical data consisting of sub-district data and the number of incidents. The research results of the Fuzzy C-means model in analyzing infectious disease trend patterns show 3 clusters. The first cluster of vulnerable areas has four sub-districts: Sawang, Syamtalira Bayu, Dewantara and Muara Batu. Then, the second cluster still consists of 18 sub-districts. Finally, the safe cluster consists of 8 sub-districts. Meanwhile, the results of the ward model research showed that there were 2 clusters, namely vulnerable consisting of 19 sub-districts and safe eight sub-districts, which were then included in the spatial map. Meanwhile, analysis of non-communicable disease patterns using fuzzy c-means, namely thalassemia and epilepsy in cluster C1 (High) in 4 and 7 sub-districts, medium cluster in 9 and 7, and low cluster in 14 and 16 sub-districts. Therefore, this research can provide an important picture for the Health Service in analyzing trends in cluster patterns of growth of infectious and non-communicable diseases in children.