Forecasting the Case Number of Infectious Diseases Using Type-2 Fuzzy Logic for a Diphtheria Case Study

Abstract

Diphtheria is an infectious disease with a high mortality rate. In Indonesia, the number of diphtheria cases has remained relatively high in recent years, so efforts to prevent and control diphtheria are needed. Forecasting of the number of diphtheria cases was carried out in this study by applying a type-2 fuzzy logic systems method. Forecasting in this study was carried out by involving the variables of the number of diphtheria sufferers, the percentage of immunization coverage comprising four immunization types, and population density. Regions are grouped into three clusters based on the number of cases that have occurred. Each cluster is taken and sampled in the form of one region to acquire a robust model for other regions. The forecasting results for the next 24 periods show that the performance of the type-2 fuzzy logic systems method is quite good, with accuracy values in the Malang area showing an MSE of 8.785 and an SMAPE of 54.91%. In the Surabaya area, the forecasting accuracy results have an MSE value of 14.940 and an SMAPE of 35.51%. In the Sumenep area, the forecasting accuracy results show an MSE value of 2.188 and an SMAPE of 67.63%. The results of the forecasting of the number of cases can be used as a guide in planning and making decisions regarding the prevention and management of diphtheria.

Keywords

• forecasting
• diphtheria
• type-2 fuzzy logic
• infectious disease