ANALISIS KECENDERUNGAN INFORMASI MENGGUNAKAN ALGORITMA HIERARCHICAL AGGLOMERATIVE CLUSTERING

Abstract

Social media is an online media where users can easily participate, share, create content or give an opinion to certain information or news. Twitter is social media that is often used by people around the world. This research has a purpose to cluster student tweets using a hierarchical agglomerative algorithm on the @unisbank account. The data of this research are tweets collected based on the hastag about Unisbank Semarang. To find out information from one another using an algorithm to calculate the eucledian distance. The result of calculation of document distances taking the center of 20 results in a total of 7 document clusters, with the largest cluster having an eucledian distance of 28.