Spatial-Temporal Visualization of Dengue Haemorrhagic Fever Vulnerability in Kediri District, Indonesia, Using K-means Algorithm

Dengue Haemorrhagic Fever (DHF) is an infectious disease that remains a major public health concern in Indonesia. Based on data from the Ministry of Health in 2019, the area with the highest number of dengue cases in East Java province is the Kediri district. The spatial and temporal heterogeneity of dengue risk, as well as the factors associated with risk variation, indicate the importance of health issues. The spatial-temporal analysis becomes an important element in preparation for early warning systems for the prevention and controlling dengue fever. This paper provides a new strategy for mapping the level of DHF vulnerability in the villages of Kediri district using the K-means method. Spatial-temporal visualization displays the distribution of DHF susceptibility areas from 2016 to 2019 based on several factors, consisting of the DHF sufferers, patients who died, population, rainfall, and public facilities. The 344 villages are divided into low, medium, and high vulnerability levels using the K-means clustering algorithm. Web-based spatial-temporal visualization is useful to compare the level of DHF vulnerability from year to year. Based on the evaluation of the silhouette coefficient average value of 0.57, it shows a fairly good clustering result.