JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Vol 4 No 1 (2022): October 2022

Classification Classification of COVID-19 Monthly Cases Using Artificial Neural Network (ANN) Method

Christina Natalia (Telkom University, Bandung)
Aniq A. Rohmawati (Telkom University, Bandung)
Sri Suryani Prasetyowati (Telkom University, Bandung)



Article Info

Publish Date
29 Oct 2022

Abstract

This study proposes the MLP type ANN method with the influence of Cross-Validation evaluation using three K-Fold tests, namely 3, 5, and 8. The data used are the data that relate to COVID-19 cases issued from the Bandung Public Health Office, climate report from Bandung Meteorological, Climatological, and Geophysical Agency (BMKG), population data from Bandung Population Office, citizen’s educational history from the Bandung Education Office and the West Java Open Data website. The data also was gathered from 151 sub-districts in Bandung City, with a total of 22 attributes collected from November 2020 to December 2021. The ANN method is included in the deep learning process. Therefore, the number of hidden layers utilized has a significant impact on the performance of the model being constructed. The implementation of Cross-Validation evaluation with K=8 results in an accuracy value of up to 98% and an error metric measurement of 0.3404 for MAE and 0.5994 for RMSE. This study's objective is to provide information on the optimal K-Fold Cross Validation parameters used in this ANN method to provide better performance during building a classification model for confirmed Covid-19 patients.

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Journal Info

Abbrev

josh

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Artikel yang dimuat melalui proses Blind Review oleh Jurnal JOSH, dengan mempertimbangkan antara lain: terpenuhinya persyaratan baku publikasi jurnal, metodologi riset yang digunakan, dan signifikansi kontribusi hasil riset terhadap pengembangan keilmuan bidang teknologi dan informasi. Fokus Journal ...