Covid-19 outbreak that scours the world nowadays is affecting all sectors, including food security. Therefore it needs to restructuring the food security policies to ensure that every people obtains adequate and nutritious food. However, the society in each province have different conditions. Thus the clusterization of food security level per province is indispensable to support strategic and policy decision in order to face the Covid-19 pandemic. This research aimed to clustering food security level of each province in Indonesia. Furthernore, this research also compare several clustering methods. The clustering method that used as a comparison in this study is K-means, DBSCAN, Louvain and Self organizing maps methods. Method with the highest silhouette coefficient value in this research will represent the results of food security clustering. The resul of the research show that K-means achieve highest silhouette coefficient value (0.568). Therefore the clusterization result of K-means chosen to represent the level of food security in this research. Further, it followed by self organizing maps with silhouette coefficient 0.559, louvain 0.312 and DBSCAN 0.15. The clusterization result show there are 7 provinces with high food security index, 24 provinces with medium food security index and 3 provinces with low food security index. This research also propose policies strategy and recommendation related to regional food security condition in order to face the Covid-19 pandemic. This research is expected to be a consideration of Indonesian government in making policies on national food security.
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