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All Journal Jurnal Civics: Media Kajian Kewarganegaraan ELINVO (Electronics, Informatics, and Vocational Education)
Nasichuddin, Moch. Ari
Unknown Affiliation
Computer Science & IT Education Electrical & Electronics Engineering Social Sciences

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Strengthening digital citizenship through discourse analysis of presidential and vice-presidential candidates in the 2024 Presidential Election Mulyono, Budi; Trilatifah, Winda; Nasichuddin, Moch. Ari; Syambudi, Irwan; Trisnawati, Diana
Jurnal Civics: Media Kajian Kewarganegaraan Vol 21, No 1 (2024)
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jc.v21i1.71620

Abstract

With the rapid advancement of information technology and increased internet access in Indonesia, citizens' participation in the digital realm has grown substantially. Digital citizens' presence is crucial in the 2024 Presidential Election, playing a pivotal role in disseminating political information, influencing public opinion, and providing support to candidates. This study examines the digital citizens' discourse on presidential and vice-presidential candidate pairs in the 2024 election in the digital public sphere. The method of issue analysis employs topic modeling with keywords "anies & muhaimin," "ganjar & mahfud," and "prabowo & gibran" on social media platform X. The research findings indicate that the discourse is clustered for each candidate pair. Narratives of support and optimism predominantly characterize the Anies-Muhaimin pair. The Ganjar-Mahfud pair exhibits clusters covering volunteer support, constitutional narratives, development aspirations, uniform buzzer narratives, and support from figures such as Yenny Wahid and advocacy for Palestine. The Prabowo-Gibran pair has clusters discussing support from the younger generation, political dynasty issues, PDIP reactions, and buzzer strategies with massive hashtags. Digital citizens engage in organized and diverse discourses regarding presidential and vice-presidential candidates, emphasizing the importance of understanding these dynamics to ensure responsible participation in the digital political process.
Topik Modeling Penelitian Dosen JPTEI UNY Pada Google Scholar Menggunakan Latent Dirichlet Allocation Nurlayli, Akhsin; Nasichuddin, Moch. Ari
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 4 No. 2 (2019): November 2019
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (612.934 KB) | DOI: 10.21831/elinvo.v4i2.28254

Abstract

The mapping of research topics for lecturers is necessary to determine the research tendencies in a department or study program. This study aims to implement topic modeling in the publication titles of the Department of Electronics and Informatics Education Engineering of Universitas Negeri Yogyakarta (JPTEI UNY) lecturers taken from Google Scholar. The method used for topic modeling is the Latent Dirichlet Allocation (LDA). LDA is a generative probabilistic model for finding the semantic structure of a corpus collection based on the hierarchical bayesian analysis. After the topic modeling process, the results showed that JPTEI UNY lecturers tend to have four research clusters consisting of vocational education, system development, learning media, and vocational learning systems.
Co-Authors Mulyono, Budi Nurlayli, Akhsin Syambudi, Irwan Trilatifah, Winda trisnawati, diana