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Record W4393208171 · doi:10.53088/jikab.v2i3.58

Pengaruh Pendapatan Asli Daerah, Pajak Daerah, dan Retribusi Daerah terhadap Belanja Modal

2023· article· id· W4393208171 on OpenAlexaff
Gilang eko Cahyanto, Darmanto Darmanto, Wikan Budi Utami

Bibliographic record

VenueJurnal Ilmiah Keuangan Akuntansi Bisnis · 2023
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
FundersUniversitas Negeri Yogyakarta
KeywordsBusiness

Abstract

fetched live from OpenAlex

Penelitian ini merupakan jenis penelitian kuantitatif yang bertujuan untuk mengetahui pengaruh Pendapatan Asli Daerah, Pajak Daerah, dan Retribusi Daerah Kabupaten dan Kota Seluru Soloraya tahun 2017-2021. Jenis data yang digunakan dalam penelitian ini adalah data sekunder yang berasal dari Laporan Realisasi Anggaran Pendapatan dan Belanja Daerah dari 6 Kabupaten dan 1 Kota seluruh soloraya. Teknik pengambilan sampel pada penelitian ini menggunakan teknik sampling jenuh. Jumlah sampel pada penelitian ini berjumlah 35 sampel. Metode analisis data yang digunakan adalah uji asumsi klasik dan uji regresi linier berganda, uji F, uji t, uji R2. Hasil uji t menghasilkan nilai Signifikansi Pendapatan Asli Deaerah sebesar 0,453, Pajak Daerah 0,006, Retribusi Daerah 0,000. Hasil uji t menghasilkan nilai signifikan Pendapatan Asli Daerah lebih besar dari 0,05 maka Pendapatan Asli Daerah tidak berpengaruh signifikan terhadap Belanja Modal. Sedangkan Pajak Daerah, dan Retribusi Daerah memiliki nilai signifikansi kurang dari 0,05 yang berarti Pajak Daerah dan Retribusi Daerah berpengaruh signifikan terhadap Belanja Modal.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0240.005

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 head0.036
GPT teacher head0.235
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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