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Record W3042749471 · doi:10.46888/flobamora.v2i1.7

Optimalisasi pendapatan asli daerah Provinsi Nusa Tenggara Timur

2019· article· id· W3042749471 on OpenAlexaff
Suci Istiqlaal

Bibliographic record

VenueFLOBAMORA · 2019
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessAgricultural scienceBusiness administrationEnvironmental science

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk mengidentifikasi besaran sumber-sumber pendapatan asli daerah, langkah-langkah yang ditempuh dalam peningkatan pendapatan asli daerah (PAD), mengeksplorasi hambatan-hambatan yang terjadi dalam optimalisasi sumber-sumber PAD, dan solusi strategis dalam optimalisasi PAD.Metode penelitiannya adalah kuantitatif dan kualitatif (mix method).Hasil penelitian menunjukkan bahwa besaran keempat sumber pendapatan asli daerah mengalami trend pendapatan yang fluktuatif selama tahun 2013-2017.Kontribusi keempat sumber pendapatan asli daerah terhadap pendapatan daerah dinilai masih rendah.Faktor-faktor penghambat optimalisasi pendapatan asli daerah Provinsi NTT terdiri dari faktor internal dan eksternal.Faktor internal meliputi budaya kelembagaan, administrasi (biaya operasional), teknologi informasi, kondisi geografis, kualitas dan kuantitas SDM.Sedangkan, faktor eksternal meliputi kepentingan politik tertentu, kondisi ekonomi masyarakat dan kesadaran masyarakat. Strategi-strategi yang telah diimplementasi dalam optimalisasi pendapatan asli daerah Provinsi NTT antara lain; strategi intensifikasi, ekstensifikasi dan peningkatan mutu pelayanan. Melalui hasil AHP, alternatif strategi yang dipilih adalah mengoptimalkan strategi inovasi.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.037

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 head0.018
GPT teacher head0.196
Teacher spread0.178 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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