Noodle Grouping Based on Nutritional Similarity with Hierarchical Cluster Analysis Method

Abstract

Everyone in the world definitely needs nutritious food. Therefore consumers must be smart in choosing nutritious foods. Noodles are a type of food that is popular in Indonesia. The purpose of this study was to classify fourteen types of noodle brands based on the similarity in the amount of nutritional content in each component. The method used in this study is a hierarchical cluster type analysis method with the SPSS software tool. The results showed that the fourteen types of noodles can be classified into clusters between two and four. Classification into two clusters shows that there are four types of noodle brands that are nutritionally similar in one cluster A and there are ten types of noodle brands that are similar in nutritional content in one cluster B.