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September 17, 2025International Journal Software Engineering and Computer Science (IJSECS)

Social Media Sentiment Analysis of Twitter Regarding People's Housing Savings (TAPERA) Using Naïve Bayes

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Authors

ADAvry Liyanah DewyMKMia Kamayani

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Overview

This study analyzes Twitter sentiment towards Indonesia's housing savings program (TAPERA) using Naïve Bayes, revealing public opinions.

Key Points

  • The sentiment analysis of 1,800 tweets showed that 65.69% express negative sentiment towards the TAPERA program.
  • The Naïve Bayes model achieved an overall accuracy of 84.17%, indicating its effectiveness in classifying sentiments.
  • Data preprocessing included rigorous cleaning and manual annotation to establish a reliable dataset for analysis.
  • The findings provide valuable insights for stakeholders to assess and improve the TAPERA program based on public sentiment.

Cite This Study

Dewy et al. (2025) studied this question.

synapsesocial.com/papers/68d4596631b076d99fa5bfefhttps://doi.org/10.35870/ijsecs.v5i2.4126
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