Implementation of K-means and Weight Product (WP) Methods in Determining Work From Home (WFH) Priorities in the New Normal Period in Indonesia

Abstract

 Covid-19 (SARS-CoV-2) is a new type of virus that began in the city of Wuhan, China in late 2019. Over time, the development of the Covid -19 Virus has greatly increased so that it has an overall impact on an organization. Currently, there are various methods in organizations that have been carried out to reduce the development of COVID-19, one of which is working from home during the New Normal period. This research aims to apply the K-Means and Weight Product (WP) methods in determining the priority of giving WFH schedules to all employees depending on the conditions of each employee. The K-Means method is used to group a number of covid-19 patient case data based on age and disease history. The output results of the process will be used as input criteria and criteria importance in the WP method. The use of the Elbow method makes it easy to determine the value of K in the clustering process on various data used. In this study, the best K value is 3 based on the evaluation results using the elbow method. The use of 2 criteria from the results of clustering covid-19 patient data in making decision models with the WP method provides more objective and precise decision results based on data / facts that have occurred. The functionality aspect of the system is very good after going through the process of testing the calculation results manually and using the system, both have the same results.