Forecasting Pneumonia Toddler Mortality Using Comparative Model
ARIMA and Multilayer Perceptron
Dublin Core
Title
Forecasting Pneumonia Toddler Mortality Using Comparative Model
ARIMA and Multilayer Perceptron
ARIMA and Multilayer Perceptron
Subject
Pneumonia, Forecasting, ARIMA, Multilayer Perceptron
Description
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.
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.
Creator
Ni Kadek Ary Indah Suryani1
, Oka Sudana2
, Ayu Wirdian
, Oka Sudana2
, Ayu Wirdian
Publisher
Universitas Udayana
Date
22-08-2022
Contributor
Fajar bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Ni Kadek Ary Indah Suryani1
, Oka Sudana2
, Ayu Wirdian, “Forecasting Pneumonia Toddler Mortality Using Comparative Model
ARIMA and Multilayer Perceptron,” Repository Horizon University Indonesia, accessed June 6, 2025, https://repository.horizon.ac.id/items/show/9205.
ARIMA and Multilayer Perceptron,” Repository Horizon University Indonesia, accessed June 6, 2025, https://repository.horizon.ac.id/items/show/9205.