Implementasi Metode K-Nearst Neighbor Berbasis Euclidean Distance Untuk Klasifikasi Penerimaan Vaksin Covid-19

The first semester of 2020 the COVID-19 pandemic took place, resulting in many countries implementing massive social restrictions. And one of the solutions provided by the government is through the regulation of the Minister of Health of the Republic of Indonesia number 84 of 2020 regarding the implementation of vaccinations in the context of dealing with the 2019 corona virus disease pandemic. This vaccine is expected to be one of the solutions to prevent transmission and prevent the risk of spreading COVID-19. This study aims to design and build an application for the classification of vaccine recipients based on their urgency according to their priority scale based on predetermined criteria and sub-criteria. Vaccination is given based on the order where priority is given to the frontline who are dealing directly with the COVID-19 pandemic. This research implements the K-Nearest Neighbor method based on Euclidean distance. This method was chosen because it is simple, easy to learn and effective in determining distance. In the process of classifying vaccine recipients, several criteria are needed, namely gender, occupation, age, pregnancy and medical history based on the results of observations and interviews that have been carried out. Then in determining the weight value for each criterion/attribute, and a ranking process is carried out which results in a decision to be used as a recommendation for the recipient of the covid-19 vaccine. Keywords: Vaccine , Covid-19, K-Nearest Neighbor , Euclid e an distance