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October 15, 2025Engineering headway

Clustering Tax Compliance Data Using k-Means Algorithm: A Study Case of Manufacturing Companies in Indonesia

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Authors

NUNur UddinUniversitas Atma Jaya MakassarADAgustine DwianikaIndonesia Open UniversityISIrma Paramita SofiaUniversitas Atma Jaya Makassar

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Implication

Observational analysis clusters tax compliance data in manufacturing companies, highlighting limitations of survey scores.

Key Points

  • The k-means algorithm clustered tax compliance data into three distinct groups, revealing patterns.
  • An evaluation indicated a small correlation between the clustering results and previous survey scores.
  • The analysis included data from 209 respondents representing finance departments across various companies.
  • The findings suggest that tax compliance is complex and cannot solely rely on survey scores for assessment.

Cite This Study

Uddin et al. (2025) studied this question.

synapsesocial.com/papers/68efd921056559ef42877398https://doi.org/10.4028/p-j36pcn
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  5. 5A Linear Time-Complexity k-Means Algorithm Using Cluster Shifting2014 · 125 citations