Prediksi Penyebaran Demam Berdarah Dangue dengan Algoritma Hybrid Autoregressive Integrated Moving Average dan Artificial Neural Network : Studi Kasus di Kabupaten Bandung

Ichwanul Muslim Karo Karo

Abstract


Dengue Fever is an infectious diseases transmitted by Aedes Aegypti mosquito. WHO (World Health Organization) has working on many preventive ways against dengue fever with the technology implementation. The technology which used to prevent the transmission of dengue fever is a set of computational process to generate a prediction of dengue fever transmission which are expected to help prevent dengue fever transmission. In order to contribute in the development of dengue fever transmission prevention technology author develop a hybrid model of Autoregressive Integrated Moving Average and Artificial Neural Network to predict dengue fever incident rate based on several variable such as weather and previous incident rate data from January 2009 – November 2016. The hybrid ARIMA and ANN output has lower error level which indicate by small RMSE value. The optimum hybrid model is ARIMA -ANN with number of order is (1,0,3) as the RMSE value is 0.0087.

Keywords


DBD; ARIMA; ANN; Incident Rate

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References


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DOI: https://doi.org/10.17509/seict.v2i2.40222

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