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Record W7117669934 · doi:10.14710/jwl.13.3.29-40

ANALISIS PENGARUH UPAH MINIMUM KABUPATEN/KOTA TERHADAP HARGA PROPERTI RESIDENSIAL TIPE KECIL

2025· article· id· W7117669934 on OpenAlexaff
Raden Nugroho Pitoro Nur Mohammad, Muhammad Halley Yudhistira

Bibliographic record

VenueJurnal Wilayah dan Lingkungan · 2025
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
Keywordsnot available

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk mengidentifikasi pengaruh perubahan Upah Minimum Kabupaten/Kota (UMK) terhadap harga properti residensial tipe kecil secara empiris. Studi ini dilatarbelakangi oleh kekhawatiran bahwa peningkatan daya beli akibat kenaikan UMK dapat mendorong kenaikan harga properti, khususnya untuk rumah tipe kecil yang menjadi sasaran kelompok berpenghasilan rendah. Penelitian ini menggunakan model fixed-effect dengan data panel dari 16 kota besar di Indonesia selama periode 2016–2022, serta sejumlah variabel kontrol seperti PDRB konstruksi, PDRB ADHK, tingkat pengangguran, dan realisasi FLPP. Hasil estimasi menunjukkan bahwa kenaikan UMK tidak berpengaruh signifikan terhadap harga properti residensial tipe kecil. Temuan ini memiliki implikasi penting terhadap kebijakan perumahan dan pengupahan, bahwa peningkatan UMK tidak serta-merta memicu lonjakan harga properti. Studi ini memperkuat literatur mengenai hubungan antara kebijakan ekonomi makro dan dinamika harga properti di Indonesia.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.026
GPT teacher head0.231
Teacher spread0.204 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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