Journal of Computing and Informatics Research
Vol 3 No 2 (2024): March 2024

Utilizing K-Means Clustering to Understanding Audience Interest in SEO-Optimized Media Content

Erlin Windia Ambarsari (Unknown)
Dedin Fathudin (Unknown)
Gravita Alfiani (Unknown)



Article Info

Publish Date
17 Mar 2024

Abstract

This study observes k-means clustering for segmenting SEO data to understand audience interests, identifying the elbow method as crucial for determining the optimal number of clusters. It highlights notable differences in content engagement across clusters, emphasizing the need for refined SEO strategies and a deeper understanding of audience segmentation. Despite challenges like SEO's dynamic nature and data reliance, this methodology provides a strong foundation for enhancing content strategies. Future research suggestions include cross-platform data integration, longitudinal studies, sentiment analysis, content experimentation, user experience (UX) focus, and monitoring algorithm updates to develop more adaptive content and SEO strategies aligned with changing audience behaviors.

Copyrights © 2024






Journal Info

Abbrev

comforch

Publisher

Subject

Computer Science & IT

Description

Fokus kajian Journal of Computing and Informatics Research mempublikasikan hasil-hasil penelitian pada bidang informatika, namun tidak terbatas pada bidang ilmu komputer yang lain, seperti: 1. Kriptografi, 2. Artificial Intelligence, 3. Expert System, 4. Decision Support System, 5. Data Mining, dan ...