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Similarity Search on Southeast Asian Food Ingredients Using Association Rule Mining
Boby Siswanto, Evawaty Tanuar, Yasi Dani, Maria E. E. Deanne

School of Computer Science, Bina Nusantara University
Jakarta, Indonesia


Abstract

Different kinds of data sources can be used for analysis- one of them is youtube. Youtube is a platform where users can share various information in video format. One of the content on youtube is cooking- many people shared how to cook and the recipe. This research aims to find the similarities of ingredients in Southeast Asia cuisine based on the YouTube video dataset. This research finding shows the similarity of several main ingredients from 999 collected data by implementing association rules mining algorithms. The research also able to find out that Myanmar, Indonesia, Brunei, and Vietnam have the highest similarity in the food ingredient compare to other countries. Therefore, for future development, it can be used to recommend the international cuisine recipe based on the ingredient

Keywords: Similarity Search, Food Ingredients, YouTube, Southeast Asia, Association Rule Mining

Topic: Computer Science

Plain Format | Corresponding Author (Boby Siswanto)

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