Long Short-Term Memory forecasting model for dengue fever cases in Malang regency, Indonesia

Nur Aini Lestari; Raras Tyasnurita; Retno Aulia Vinarti; Wiwik Anggraeni

doi:10.1016/j.procs.2021.12.131

Long Short-Term Memory forecasting model for dengue fever cases in Malang regency, Indonesia

Nur Aini Lestari
, Raras Tyasnurita^*
, Retno Aulia Vinarti
, Wiwik Anggraeni

^*Corresponding author for this work

Institut Teknologi Sepuluh Nopember

Research output: Contribution to journal › Conference article › peer-review

4 Citations (Scopus)

Abstract

Dengue Hemorrhagic Fever (DHF) tends to increase in the number of cases every year. East Java Province is one that contributes the most to the number of dengue cases, especially Malang Regency. One action that can be taken is to predict the number of dengue cases. This study aims to forecast the number of dengue cases using Long Short-Term Memory method. The model formation process in Kepanjen Sub-district produced the best accuracy with Root Mean Squared Error (RMSE) value of 5.5922 and Symmetric Mean Absolute Percentage Error (SMAPE) value of 34.429% which was carried out by involving the humidity factor.

Original language	English
Pages (from-to)	180-188
Number of pages	9
Journal	Procedia Computer Science
Volume	197
DOIs	https://doi.org/10.1016/j.procs.2021.12.131
Publication status	Published - 2021
Event	6th Information Systems International Conference, ISICO 2021 - Virtual, Online, Italy Duration: 7 Aug 2021 → 8 Aug 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Dengue hemorrhagic fever
Forecasting
Long short-term memory
Malang regency

Access to Document

10.1016/j.procs.2021.12.131

Cite this

@article{e7d6e1450943463f96752636beabb8dd,

title = "Long Short-Term Memory forecasting model for dengue fever cases in Malang regency, Indonesia",

abstract = "Dengue Hemorrhagic Fever (DHF) tends to increase in the number of cases every year. East Java Province is one that contributes the most to the number of dengue cases, especially Malang Regency. One action that can be taken is to predict the number of dengue cases. This study aims to forecast the number of dengue cases using Long Short-Term Memory method. The model formation process in Kepanjen Sub-district produced the best accuracy with Root Mean Squared Error (RMSE) value of 5.5922 and Symmetric Mean Absolute Percentage Error (SMAPE) value of 34.429\% which was carried out by involving the humidity factor.",

keywords = "Dengue hemorrhagic fever, Forecasting, Long short-term memory, Malang regency",

author = "Lestari, \{Nur Aini\} and Raras Tyasnurita and Vinarti, \{Retno Aulia\} and Wiwik Anggraeni",

note = "Publisher Copyright: {\textcopyright} 2021 The Authors. Published by Elsevier B.V.; 6th Information Systems International Conference, ISICO 2021 ; Conference date: 07-08-2021 Through 08-08-2021",

year = "2021",

doi = "10.1016/j.procs.2021.12.131",

language = "English",

volume = "197",

pages = "180--188",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Long Short-Term Memory forecasting model for dengue fever cases in Malang regency, Indonesia

AU - Lestari, Nur Aini

AU - Tyasnurita, Raras

AU - Vinarti, Retno Aulia

AU - Anggraeni, Wiwik

PY - 2021

Y1 - 2021

N2 - Dengue Hemorrhagic Fever (DHF) tends to increase in the number of cases every year. East Java Province is one that contributes the most to the number of dengue cases, especially Malang Regency. One action that can be taken is to predict the number of dengue cases. This study aims to forecast the number of dengue cases using Long Short-Term Memory method. The model formation process in Kepanjen Sub-district produced the best accuracy with Root Mean Squared Error (RMSE) value of 5.5922 and Symmetric Mean Absolute Percentage Error (SMAPE) value of 34.429% which was carried out by involving the humidity factor.

AB - Dengue Hemorrhagic Fever (DHF) tends to increase in the number of cases every year. East Java Province is one that contributes the most to the number of dengue cases, especially Malang Regency. One action that can be taken is to predict the number of dengue cases. This study aims to forecast the number of dengue cases using Long Short-Term Memory method. The model formation process in Kepanjen Sub-district produced the best accuracy with Root Mean Squared Error (RMSE) value of 5.5922 and Symmetric Mean Absolute Percentage Error (SMAPE) value of 34.429% which was carried out by involving the humidity factor.

KW - Dengue hemorrhagic fever

KW - Forecasting

KW - Long short-term memory

KW - Malang regency

UR - https://www.scopus.com/pages/publications/85123806368

U2 - 10.1016/j.procs.2021.12.131

DO - 10.1016/j.procs.2021.12.131

M3 - Conference article

AN - SCOPUS:85123806368

SN - 1877-0509

VL - 197

SP - 180

EP - 188

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 6th Information Systems International Conference, ISICO 2021

Y2 - 7 August 2021 through 8 August 2021

ER -

Long Short-Term Memory forecasting model for dengue fever cases in Malang regency, Indonesia

Abstract

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this