Forecasting Pneumonia Toddler Mortality Using Comparative Model
ARIMA and Multilayer Perceptron

Forecasting Pneumonia Toddler Mortality Using Comparative Model
ARIMA and Multilayer Perceptron

Pneumonia, Forecasting, ARIMA, Multilayer Perceptron

Pneumonia is an inflammatory lung disease that causes the second largest number of deaths in Indonesia after Dengue
Hemorrhagic Fever (DHF). In 2021, there was an increase in cases of 7.8% compared to the previous year, and was
exacerbated by the Covid-19 pandemic. Predictive methods were needed to predict and compare the ARIMA and MLP methods,
where the results of the best methods were selected for long-term forecasting. The research data used was from January 2014
– December 2021, with a total of 96 data. In choosing the best method, the basic error calculations used were Mean Absolute
Deviation, Mean Squared Error, and Mean Absolute Percentage Error. This study aims to build a predictive model for the next
period of pneumonia under-five mortality. These results can be used for government policy-making related to mortality
prevention for the next period. The results showed that the MLP method was superior to ARIMA. Testing 28 mortality rate data
using the final test result showed that the best method was MLP, with a hidden layer value of 2.2, a learning rate of 0.3, and
an error percentage of 1.27%. The prediction results of the overall mortality rate of pneumonia under five in 2022 was
predicted to be 136 people.

Ni Kadek Ary Indah Suryani1
, Oka Sudana2
, Ayu Wirdian

Universitas Udayana

22-08-2022

Fajar bagus W

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Indonesia

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