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Alistin, Zharifah Dhiya Ayu
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Analisis Sentimen dan Pemodelan Topik Opini Publik Terkait Data Badan Pusat Statistik Tahun 2024 Rahman, Dimas Haafizh; Alistin, Zharifah Dhiya Ayu; Pramana, Setia
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2365

Abstract

The role of BPS has become increasingly crucial with the rising demand and sources of data over time. The quality of BPS data is evaluated through the Data Needs Survey (SKD). The 2024 SKD indicates that 98.16% of consumers are satisfied with the quality of BPS data. However, this evaluation only involved data consumers from BPS PST, and there remains a time gap between the implementation and dissemination of the survey results. Social media platform X, which is popular in Indonesia, allows its users to express their opinions through tweets. This research is conducted to understand public sentiment, identify the best classification model, and discover topics discussed by the public regarding BPS data based on tweets from the X platform in 2024. The tweets were taken through labeling and preprocessing before applying Machine Learning methods to classify public sentiment. The Support Vector Machine (SVM) method, with a weighted average of 0.68, performed best compared to Naïve Bayes, Rocchio Classification, and K-NN in modeling public opinion sentiment. The implementation of LSA and LDA discovered topics consisting of public opinions and issues related to BPS data such as poverty rate manipulation and BPS data as a credible source.
Co-Authors Pramana, Setia Rahman, Dimas Haafizh