Track: COVID-19 Competition

Abstract

Covid-19 is a contagious disease caused by SARS-CoV-2, which is a type of coronavirus. Since its appearance at the end of 2019, until 2 August 2020, there have been more than 17.7 million infected people worldwide. During that time, various studies appeared to study the Covid-19 pandemic. One of them was research on the development of the number of Covid-19 cases. One of the many datasets used to study the development of Covid-19 cases is data from the "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University". The purpose of this study is to analyze the quality of the data and detect errors that occur in the data so that researchers who will use it know the quality of the data before using them. This study uses a statistical quality control approach. The methods used in this study are acceptance sampling and control charts. 30% of the data will be issued using a control chart and investigated for any possible errors. After that, the data is corrected according to the error that occurred. This process is repeated until there are no more errors in the data. After several iterations, we found errors in the Covid-19 data in this study. The errors found are data input errors, decreasing value, confirm data is less than recover, confirm data is less than death, zero confirm on the first date, not zero recovers on the first date, and not zero death on the first date. It is recommended for those who will use the data from this source to check and correct them first before using them.