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Record W4389290308 · doi:10.14710/jpk.11.1.26-36

POTENSI PENGEMBANGAN KAWASAN BERBASIS TOD PADA KAWASAN STASIUN PASAR SENEN

2023· article· id· W4389290308 on OpenAlexaff
Ananda Rizky Nur Faiza, Rahel Situmorang, Martina Cecilia Adriana

Bibliographic record

VenueJurnal Pengembangan Kota · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsForestryPhysicsGeography

Abstract

fetched live from OpenAlex

TOD merupakan perencanan kawasan berkelanjutan yang mengintegrasikan antara kebutuhan transportasi dengan efisiensi lahan perkotaan. Kawasan Senen merupakan salah satu kawasan strategis di Jakarta karena merupakan pusat kegiatan sekunder dan juga Pusat Pelayanan Kota. Melalui RDTR DKI Jakarta 2022 dan Perpres No 60 tahun 2020 tentang Rencana Tata Ruang Kawasan Perkotaan Jabodetabekpunjur, Stasiun Pasar Senen ditetapkan sebagai TOD Kota. Penelitian ini bertujuan untuk mengukur potensi eksisting Kawasan Stasiun Pasar Senen sebagai kawasan TOD kota. Pengukuran dilakukan dengan menghitung TOD Indeks yang berasal dari indikator–indikator utama dalam perancangan kawasan TOD. Hasil dari penelitian ini menunjukkan bahwa Kawasan Stasiun Pasar Senen belum optimal sebagai TOD Kota. Nilai TOD indeks Kawasan Stasiun Pasar Senen adalah 0.63 yang tergolong cukup tinggi melebihi 0.5 namun masih jauh dari nilai optimal TOD. Kondisi saat ini masih jauh dari prinsip-prinsip TOD, khususnya pada kepadatan kawasan serta infrastruktur pejalan kaki. Pengembangan TOD Kawasan Stasiun Pasar Senen perlu memaksimalkan fungsi lahan campuran dan penyediaan infrastruktur pejalan kaki.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0030.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.034
GPT teacher head0.295
Teacher spread0.261 · 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 designNot applicable
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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