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Record W3171744362 · doi:10.5267/j.ac.2021.5.002

Determinants of personal tax compliance

2021· article· en· W3171744362 on OpenAlexvenueno aff
Subadriyah Subadriyah, Puji Harto

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTaxpayerBusinessSanctionsRevenueTax revenuePopulationCompliance (psychology)Public economicsAccountingEconomicsPolitical sciencePsychologyEnvironmental health

Abstract

fetched live from OpenAlex

The largest state revenue comes from taxes. Even though the number of taxpayers is increasing from year to year, the tax revenue in Indonesia is still relatively low, since taxpayer compliance is still low. This study aims to determine the factors that influence individual taxpayer compliance in paying taxes at Jepara, Indonesia. The study uses a quantitative approach with a population of individual taxpayers who are registered at the tax office of Jepara, Indonesia. The number of samples is obtained by 100 respondents using the Slovin formula. The sampling technique was a convenience sampling technique. The data analysis method used is multiple regression analysis and Moderated Regression Analysis (MRA). Based on the test, it is found that the quality of tax authorities service, understanding and knowledge of taxation, tax sanctions, tax socialization, taxpayer awareness and perceptions of tax effectiveness have an influence on taxpayer compliance. In addition, the employment status of Civil Servants is more compliant in paying taxes since their income tax has been routinely deducted by the employer on the paid income.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.268
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

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