Spatial Mapping and Prediction of Diphtheria Risk in Surabaya, Indonesia, Using the Hierarchical Clustering Algorithm

Diphtheria cases in the city of Surabaya from 2015 to 2018 have increased every year. This disease can be prevented by immunizing DPT 1, DPT 2, and DPT 3 (Diphtheria, Tetanus Pertussis) given to school-age children. Immunization is the most dominant factor, where children who do not receive DPT immunization are five times more likely to be infected with diphtheria compared to children who are immunized. This paper proposes a new approach to diphtheria risk analysis in Surabaya based on multiple criteria, including DPT immunization, number of diphtheria sufferers, and population density using the hierarchical clustering algorithm. Information is presented in the form of spatial mapping of each urban village in Surabaya, Indonesia, thus, it can present information in a smaller scope. The hierarchy clustering average linkage algorithm achieves the smallest average variance value 3.3 × 10⁻⁵ and better than single linkage and complete linkage for 2016, 2017, and 2018. This developed application also provides a prediction of the next year’s diphtheria risk level. The results of the 2019 predictions show a better diphtheria risk level of vulnerability using a single linkage rather than average linkage and complete linkage with the smallest variance 4.43 × 10⁻⁵. which shows very good clustering results. The results of the knowledge shown in this application can be used as a decision support analysis for early vigilance in diphtheria in efforts to prevent and monitor diphtheria in Surabaya.