Implementation of Least Mean Square Adaptive Algorithm on Covid-19 Prediction

This study used Corona Virus Disease-19 (Covid-19) data in Indonesia from June to August 2021, consisting of data on people who were infected or positive Covid-19, recovered from Covid-19, and passed away from Covid-19. The data were processed using the adaptive LMS algorithm directly without pre-pr...

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Bibliographic Details
Main Authors: Sri Arttini Dwi Prasetyowati, Munaf Ismail, Badieah Badieah
Format: Article
Language:Indonesian
Published: Universitas Muhammadiyah Purwokerto 2022-05-01
Series:Jurnal Informatika
Subjects:
Online Access:http://jurnalnasional.ump.ac.id/index.php/JUITA/article/view/11963
Description
Summary:This study used Corona Virus Disease-19 (Covid-19) data in Indonesia from June to August 2021, consisting of data on people who were infected or positive Covid-19, recovered from Covid-19, and passed away from Covid-19. The data were processed using the adaptive LMS algorithm directly without pre-processing cause calculation errors, because covid-19 data was not balanced. Z-score and min-max normalization were chosen as pre-processing methods. After that, the prediction process can be carried out using the LMS adaptive method. The analysis was done by observing the error prediction that occurred every month per case. The results showed that data pre-processing using min-max normalization was better than with Z-score normalization because the error prediction for pre-processing using min-max and z-score were 18% and 47%, respectively.
ISSN:2086-9398
2579-8901