Raretha Maren
State University of Malang

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce Aisyah Larasati; Raretha Maren; Retno Wulandari
Jurnal Teknik Industri Vol. 23 No. 2 (2021): Dec 2021
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.23.2.111-120

Abstract

The massive increases in textual data from Twitter and text analytics simultaneously have driven organizations to obtain hidden insights to implement the proper marketing strategies for businesses. The vast information generated by Twitter enables most e-commerce businesses to utilize Twitter to implement social media marketing. One of those e-commerce businesses is Blibli Indonesia. Intense business competition has led them to perform marketing strategies to understand consumer tendencies. Focusing the marketing strategies on consumer preferences enables the increase of consumer interest in Blibli, which is in line with enhancing the opportunity to reach new consumers. This research aims to discover Twitter content based on k-means results to cluster the tweets of @bliblidotcom. The best cluster is determined with the elbow method by selecting the deepest curvature, three clusters. The result suggests that Twitter users like Park Seo Jun's content. Hence, Blibli can focus on that content as its business marketing strategy on the Twitter platform.