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Stance Analysis of Policies Related to Emission Test Obligations using Twitter Social Media Data Dwi Retnoningrum; Dea Annisayanti Putri; Indra Budi; Aris Budi Santoso; Prabu Kresna Putra
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.69004

Abstract

Social media is currently widely used to disseminate various kinds of information, whether expressing feelings, or opinions. Public opinion is no exception regarding government policies and the implementation of emission tests, which describe the conditions that exist in society. Information on public opinion data obtained through social media in real time can assist the government in evaluating policies and improving the quality of currently implemented policies, particularly evaluating the implementation of emission tests on motorized vehicles. In this research, the application of stance analysis is used to evaluate emission test policies based on public opinion.In addition, this research aims to combine several machine learning methods and feature extraction methods to find the best combination based on accuracy, training time, and prediction time based on emission test policies. The best model based on the level of accuracy is a combination of Decision Tree and BERT, which reaches a value of 66%. Meanwhile, based on training time, the model that has the advantage is the Ridge Classifier with fasttext text representation. Based on prediction time, there are 3 combination models, namely Decision Tree with word2vec, SVM with Word2Vec, and Logistic Regression with fasttext text representation.
The Role of Social Media in Shaping Social Movements: A Case Study of #Daruratreformasi In Indonesia Using Text Mining and Network Analytics Alifdaffa Nurfahmi Dekatama; Devin Prayogo; Indra Budi; Prabu Kresna Putra; Aris Budi Santoso
Eduvest - Journal of Universal Studies Vol. 5 No. 7 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i7.51376

Abstract

The social movement #DaruratReformasi emerging in Indonesia since July 2024 has attracted widespread attention both nationally and internationally. This study aims to analyze the communication dynamics and interaction patterns within the social media network of the movement using text mining and network analytics approaches. Topic modeling identifies the dominant key issues in public discourse, while social network analysis reveals the main actors and influencers involved in information dissemination and public opinion formation. A modularity approach is employed to detect naturally formed discussion communities within the network, and temporal analysis illustrates the phases of the movement’s development from initiation to its peak in November 2024. The results indicate that social media serves as a strategic platform for social mobilization and political advocacy, with key actors distributed across interconnected communities. Additionally, the involvement of government institutions as central actors highlights the two-way communication dynamics within the digital public sphere. These findings underscore the urgency of understanding social network structures in the context of modern digital social movements and provide implications for public communication management and mass mobilization strategies in the digital era.