Prediction System for the Spread of Corona Virus in Central Java with K-Nearest Neighbor (KNN) Method

Fitriyadi, Farid and Muqorobin, Muqorobin (2021) Prediction System for the Spread of Corona Virus in Central Java with K-Nearest Neighbor (KNN) Method. International Journal of Computer and Information System (IJCIS), 2 (3). pp. 80-85. ISSN e-ISSN : 2745-9659

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Abstract

Corona Virus is currently spreading very rapidly in many parts of Indonesia, including Central Java Province. According to the current data of corona database in Central Java, today on 17th of August 2021, the number of confirmed cases is; Confirmed in Treatment (Active Cases): 16.344, Confirmed Recovered: 408.697, and Confirmed Dead: 29.148. Therefore, the total number of cases is 454.189, obtained from the sum of the number of being treated, recovered, and dead. Corona Virus is a collection of viruses that can infect the respiratory system, generally mild, such as common cold, although, some forms of diseases like; SARS, MERS, and COVID-19 are more deadly. In anticipating this case, the government has created some policies which include; limiting activities outside the house, having school activities done from home, working from home, and even having religious activities done from home too. The purpose of this study was to predict the possible rate of new cases in one of Central Java areas with confirmed cases of corona virus. Thus, it can be used as information material for the public to anticipate early. The research method applied in this research is problem analysis and literature study, data collection and implementation. The application of the K-Nearest Neighbor (KNN) method is expected to be able to predict the level of spread of COVID-19 in Central Java. The results of the research on testing the prediction system for the new cases level were tested in the Sragen area. Testing is carried out by taking samples for new cases, namely Kudu Regency/City, Confirmed: 17,599, Treated: 89, Recovered: 18,303, Died: 1,721, Suspected: 87 and Discarded Suspected: 1,711. After doing the prediction with K-NN algorithm, it showed the Condition: High.

Item Type: Article
Subjects: L Education > L Education (General)
Divisions: Fakultas Sains, Teknologi dan Kesehatan > Informatika
Depositing User: Mr Farid Fitriyadi
Date Deposited: 07 Sep 2021 01:47
Last Modified: 07 Sep 2021 01:47
URI: https:///id/eprint/1397

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