K-Means Clustering Video Trending di Youtube Amerika Serikat

Abstract

Youtube is the most popular video platform in the world today. Successful YouTubers can create videos that are widely viewed by many Youtube users around the world. A lot of viral videos on Youtube came from the United States. But, making viral videos on Youtube is a tough challenge, both for seasoned YouTubers and especially for new YouTubers. This research focuses on discovering the properties of these viral videos by clustering them into distinct clusters. K-Means algorithm is used for the clustering process. The purpose of this clustering process is to look for patterns in the data that were previously unseen. The result shows that the videos are divided into three clusters which are built from 3 variables; views, likes and dislikes. The patterns and insights found in this study can be useful for aspiring video makers who want to achieve success as a Youtuber.