West Java was the province with the highest unemployed rate during the COVID-19 pandemic. Significant increase of open unemployment rate in West Java negatively impacts the national income. This study aims to apply the clustering method using the k-means algorithm to determine priority clusters in West Java Province by looking at the number of clusters in West Java’s city and the main characteristic of each cluster. The clustering was conducted utilizing a k-means clustering algorithm which is grouping data based on similar characteristics. The clustering results were evaluated using silhouette method. The results indicated that two clusters were optimal. The clustering process using the k-means method showed that there were three clusters distinguishing the open unemployment rate during the pandemic in West Java Province in 2020. Cluster 1 had a fairly low open unemployment rate due to the stalled service sector and low minimum city wage. Cluster 2 had a high open unemployment rate due to the service sector and high minimum city wage. Cluster 3 had medium open unemployment rate due to the service sector and also medium minimum city wage. It suggests that cluster 2 is a priority cluster in dealing with the open unemployment rate.