Association Rules Mining for Identifying Popular Ingredients on YouTube Cooking Recipes Videos
Boby Siswanto, Putri Thariqa · 2018
YouTube provides a lot of videos that will be able to create dataset. YouTube video has some characteristics on number of views, likes, dislikes and comments. Association rules mining able to find the most dominant item in a dataset. This research investigates 40 random videos on YouTube by implementing association rules mining algorithm to find what is the most ingredients used in Indonesia cooking recipes. This research found that the most liked video use 2 main ingredient which are garlic and onion. This research also implements IST-EFP algorithm for reducing the dimensional of the dataset without loss on important rules obtained. This research found IST-EFP able to reduce 19% on dataset dimension with 0.7% loss on rules obtained.