Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Data Mining and Information Systems
Putri, Kinanti Anindia
Unknown Affiliation
Computer Science & IT

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

Found 1 Documents
Search

 1 
Analisis Persepsi Publik Terhadap Pilkada Jakarta 2024 dengan Clustering dan Sentimen pada Artikel Berita Zavira, Anggi Nur; Fathiyarahmani, Ilma; Nadhifa, Khansa; Putri, Kinanti Anindia; Mulyadi, Widya Amanda; Syawaliana, Zalfa
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 1 (2025): February 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i1.3812

Abstract

This study analyzes the pattern of mass media coverage related to the 2024 Jakarta Gubernatorial Election using a text mining approach with the K-Means Clustering algorithm and Lexicon-based sentiment analysis. Data were obtained through web scraping from Google News RSS Feeds, resulting in 100 articles that were analyzed after undergoing preprocessing processes such as tokenizing, filtering, and stemming. The K-Means algorithm was used to cluster the articles into eight clusters based on dominant themes, such as political support, candidacy failures, and strategic issues related to the election. This algorithm works by calculating the distance between data points and centroids, which are continuously updated until an optimal cluster is achieved based on the Silhouette Score method. Sentiment analysis revealed that most articles had a neutral sentiment, reflecting media objectivity, although some clusters showed positive and negative sentiments, indicating potential bias in the coverage. These findings provide insights into the role of media in shaping public opinion and the influence of news coverage on public perceptions in the democratic process. This study is expected to enhance political literacy among the public and encourage more critical participation, while also opening opportunities for further development of analysis methods to better understand media bias
Co-Authors Fathiyarahmani, Ilma Mulyadi, Widya Amanda Nadhifa, Khansa Syawaliana, Zalfa Zavira, Anggi Nur