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All Journal Pelita Eksakta Journal of Data Mining and Information Systems
Putri, Kinanti Anindia
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Mathematics Physics Other

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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
Effectiveness of Data Visualization Training for Junior and Senior High School Teachers to Improve Scientific Article Writing Competence Santi, Vera Maya; Rahayu, Widyanti; Arafiyah, Ria; Ladayya, Faroh; Hashifah, Zahrah; Sarwa, Amira Basyila; Putri, Kinanti Anindia; Nurkhotimah, Siti Fadilah; Ul Aliyah, Ayda Syifa
Pelita Eksakta Vol 9 No 1 (2026): Pelita Eksakta, Vol. 9, No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol9-iss1/335

Abstract

This community service program aims to enhance the scientific article writing competence of junior and senior high school teachers in Sukabumi Regency through training on data presentation and visualization using Microsoft Excel with the Data Analysis Add-Ins. The initiative was designed to address teachers’ limited statistical skills, low technological literacy, and challenges in processing and interpreting data for research activities. Conducted online in two sessions, the training included material delivery, software demonstrations, and pre- and post-training assessments. The results indicate a significant improvement in participants’ knowledge, as evidenced by the paired t-test yielding a p-value of 0.00. Thematic analysis of open-ended responses further revealed positive perceptions regarding the training’s relevance, clarity, and usefulness in strengthening statistical understanding. Overall, the program effectively improved teachers’ competencies in data analysis and scientific writing, while participants also expressed the need for more advanced training related to educational media and professional development
Co-Authors Arafiyah, Ria Fathiyarahmani, Ilma Hashifah, Zahrah Ladayya, Faroh Mulyadi, Widya Amanda Nadhifa, Khansa Nurkhotimah, Siti Fadilah Sarwa, Amira Basyila Syawaliana, Zalfa Ul Aliyah, Ayda Syifa Vera Maya Santi Widyanti Rahayu Zavira, Anggi Nur