Comparison K-Medoids Algorithm and K-Means Algorithm for Clustering Fish Cooking Menu from Fish Dataset

Abstract The production of fish-based food processing has become a commodity for restaurants, catering and home consumption, but there are still many people who don’t know how fish can be processed in various dishes their daily needs. To find out to make dishes, the researchers provide solution cooking any kind food, starting from grouping types basic ingredients that must prepared, cook them, address link with fish. This study aims so menus whose come research uses clustering algorithm, k-means k-medoids. stages this consisted data collection, selection, modeling, training, testing evaluation. object menu 978 datasets dishes. used relating attributes number likes via website, dataset is sourced https://ipm.bps.go.id/data/dataset/ikan. From two algorithms, best accuracy results -1.777 while -1.535 obtained k-medoids algorithm.