Published: 2025-08-01
Social Media Sentiment Analysis of Twitter Regarding People's Housing Savings (TAPERA) Using Naïve Bayes
DOI: 10.35870/ijsecs.v5i2.4126
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Abstract
The advancement of technology has transformed how people interact and express opinions on social media platforms. This research examines Twitter conversations regarding Indonesia's government-initiated Housing Savings Program (TAPERA) through sentiment analysis. The study employed Naïve Bayes classification methodology, with data acquisition conducted via Google Colab platform utilizing the tweet-harvest library. The collection process yielded 1,800 tweets matching predetermined search parameters. Data underwent rigorous preprocessing, including text cleaning and manual sentiment annotation to establish reliable training datasets. Examination of 720 test tweets revealed 473 (65.69%) expressed negative sentiment while 247 (34.31%) conveyed positive sentiment toward the program. The implemented Naïve Bayes model achieved 84.17% accuracy, with negative class precision at 88.71% and recall at 88.60%, while positive class precision reached 78.54% with 76.08% recall. Results indicate the Naïve Bayes approach effectively categorizes public sentiment regarding the TAPERA program, offering valuable feedback for stakeholders responsible for program assessment and enhancement.
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Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 2 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ijsecs.v5i2.4126
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Avry Liyanah Dewy
Informatics Engineering Study Program, Faculty of Industrial Engineering and Informatics, Universitas Muhammadiyah Prof. Dr. Hamka, South Jakarta City, Special Capital Region of Jakarta, Indonesia
Mia Kamayani
Informatics Engineering Study Program, Faculty of Industrial Engineering and Informatics, Universitas Muhammadiyah Prof. Dr. Hamka, South Jakarta City, Special Capital Region of Jakarta, Indonesia
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