MétaCan
Menu
Back to cohort
Record W2174342702 · doi:10.31543/jii.v1i1.58

Kajian Tingkat Pemahaman Aparat Daerah Dalam Penerapan Dan Pelaksanaan Rencana Tata Ruang Wilayah (RTRW)

2015· article· id· W2174342702 on OpenAlexaff
Anna Karenina Astiti

Bibliographic record

VenueJurnal IPTEK · 2015
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Penataan ruang merupakan suatu alat yang dapat mengurangi kesenjangan pertumbuhan antarwilayah, menterpadukan antar sektor dan mensinkronisasikan program pembangunan yangberwawasan lingkungan serta berkelanjutan. Peran yang begitu besar dari penataan ruang dalamproses pembangunan sangat diperlukan kesiapan aparatur pemerintah khususnya aparatur Pemerintah Daerah dalam memahami substansi rencana tata ruang wilayah beserta turunannya yanglebih operasional. Penelitian ini bertujuan untuk mendapatkan gambaran mengenai pemahaman aparat daerahdalam memahami substansi rencana tata ruang wilayah beserta turunannya. Metode penelitian yangdigunakan adalah kualitatif deskripsi melalui diskusi dengan responden dan penyebaran kuesioner.Hasil dari kuesioner, diperoleh sebagian aparat cukup memahami substansi rencana tata ruang danturunannya, namun kurang pemahaman terhadap luasan wilayah perencanaan. Selain itu, hanya sekitar 33% responden (aparat) yang terlibat dalam perencanaan memiliki pendidikan penataanr uang. Adapun dari hasil diskusi, diperoleh bahwa persoalan deliniasi luasan wilayah perencanaanmenjadi persoalan dan kendala.  Disamping itu juga dengan kedalaman muatan rencana rinci.Persoalan ini muncul akibat belum adanya pedoman penyusunan rencana rinci. Berdasarkan hasil tersebut diatas, maka dalam penerapan penyelenggaraaan penataan ruang yang lebih operasional dibutuhkan pedoman penyusunan rencana rinci yang ringkas langsung padapersoalan-persoalan substansial yang dihadapi aparat dalam menyusunnya. Kriteria deliniasi luasanwilayah harus secara tegas dicantumkan agar dapat memudahkan dalam penentuan penyusunan danpenyediaan dana.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.068
GPT teacher head0.241
Teacher spread0.173 · 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.

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJurnal IPTEKSame topicEconomic Growth and Fiscal PoliciesFrench-language works237,207