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All Journal Journal of Software Engineering Ampera
Yulianita Purnamasari
Universitas Bina Darma
Computer Science & IT

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Pemanfaatan Data Mining Dalam Memprediksi Kasus Positif Covid-19 Di Kota Palembang Menggunakan Algoritma K-Nearest Neighbors Yulianita Purnamasari; Yessi Novaria Kunang
Journal of Software Engineering Ampera Vol. 2 No. 2 (2021): Journal of Software Engineering Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalsea.v2i2.128

Abstract

Covid-19 was first detected in Indonesia in early March 2020. The province of South Sumatra has more than 20,000 confirmed cases of Covid-19, 15,914 from Palembang City. The Covid-19 pandemic still shows no signs of ending. This can be seen from the increase in positive cases of Covid-19 every day. In making decisions on policies and decisions related to handling Covid-19, positive cases are still an important influence in this regard. Therefore, it focuses on predicting positive cases of Covid-19 in Palembang City. The data used in this study are data taken from the official website of the Palembang City Health Office as many as 153 data with 14 parameters. From 153 data, it is divided into 80% training data and 20% testing data. The variable used in this study is the daily number of confirmed cases of Covid-19 in Palembang City. KNN is used as a model to make predictions. From the research conducted, the RMSE results were 209,362. The results of this prediction can be used as input for research related to the prediction of positive cases of Covid19 in the city of Palembang.
Co-Authors Yessi Novaria Kunang