Implementation of Fuzzy Inference System for Classification of Dengue Fever on the villages in Malang

Dengue fever is a disease that must be watched out and early preventive measures are taken so the spread of this disease can be reduced. An early preventive dengue fever can be controlled by a mathematical model. The article proposes a model of fuzzy inference system with optimal fuzzy rule bases generated by fuzzy c-means and optimized by ordinary least square (OLS). The developing system is done by forming a data structure in the form of input-output pairs. Factors that influence the number of dengue fever cases are used as the system input and the number of dengue fever cases as the system output. Based on the input-output pairs, the fuzzy rule bases is generated by using the fuzzy c-means method. The consequent part of the rule bases is optimized by the OLS method to produce the optimal rule bases. The resulted system is able to predict the level of dengue fever in the villages with an accuracy of 90% and can be used to predict the level of dengue fever in a village by inputting factors that influence the level of dengue fever.