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The health sector in developing countries such as the State of Indonesia is still experiencing problems to find out the distribution of areas prone to tropical infectious diseases, including diphtheria and tetanus. The purpose of the discussion in this paper is to perform spatial analysis of geographical information system (GIS) fields through spatial data modeling for classification of diphtheria and tetanus-prone areas based on spatial parameters of datasets such as immunization status coverage, PD3I, epidemics, nutrition status, and population density. The Weighted sum model (WSM) method is used in the process of spatial analysis which is a multiple criteria decision making (MCDM). The classification results of diphtheria and tetanus-prone areas consist of good, fair, and poor categories. Preference values are generated using the Guttman method as a basis for spatial analysis in the next series of data. The test results can be used as recommendations in policymaking to anticipate the distribution of areas in the poor category.

Weighted sum model for Spatial Analysis in Classification of Areas Prone to Diphtheria Tetanus