Dengue fever is a communicable disease that has been a big concern in Indonesia. This disease has spread out across Indonesia, including Malang Regency. Local Government and Public Health Service in Malang Regency has made various efforts including prevention and socialization, however the number of casualties caused by dengue fever are still high. Forecasting the number of dengue fever cases is very important for the local Public Health Service. It can help policy planning of disease prevention and patient care in the future. Delays in preventive measures, increasing casualties, lack of treatment facilities are the problems that can be avoided through better policy planning. In this research, Fuzzy Inference System (FIS) is used to predict number of dengue fever cases in Malang. FIS tends to have small error values and high accuracy due to detailed attention to all variables. Fuzzy Inference System does not require a lot of data and a long periods of time. The model is constructed by grouping the number of monthly dengue fever cases from the previous years based on geographical location. Population density is added as external variables of the model. The data is divided into training set, testing set, and validating set with the ratio of 70:20:10. This research shows that forecasting model based on FIS shows a good results in forecasting with MAPE 6% in lowlands, 12% in mediumlands, and 14% in highlands.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalJournal of Theoretical and Applied Information Technology
Issue number1
Publication statusPublished - Jan 2017


  • Dengue fever
  • Disease
  • Forecasting
  • Fuzzy Inference System
  • MAPE


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