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Record W4294265749 · doi:10.25104/mtm.v20i1.2145

Jalur Kereta Api Parangtritis – Bandara Yogyakarta International Airport (YIA) sebagai Pendukung Mobilitas, Pariwisata, dan Angkutan Barang

2022· article· id· W4294265749 on OpenAlexaff
Nur Budi Susanto, Imam Muthohar, Suryo Hapsoro Tri Utomo

Bibliographic record

VenueJurnal Transportasi Multimoda · 2022
Typearticle
Languageid
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessTransport engineeringBusiness administrationComputer scienceEngineering

Abstract

fetched live from OpenAlex

Sebagai salah satu perwujudan konsep “among tani dagang layar” pada pengembangan wilayah sisi selatan Bandara Daerah Istimewa Yogyakarta (DIY), Pemda DIY berencana mengembangkan jalur kereta api Parangtritis – Bandara Kulon Progo untuk mendukung mobilitas masyarakat, memajukan perekonomian, dan mendorong pengembangan pariwisata. Artikel ini bertujuan untuk melakukan kajian jalur kereta api Parangtritis – Bandara YIA sebagai pendukung mobilitas, pariwisata, dan angkutan barang. Kajian titik simpul multimoda dilakukan dengan mempertimbangkan Rencana Induk Perkeretaapian Provinsi 2017-2036, RTRW DIY Tahun 2019-2039, Rencana Induk Transportasi DIY, serta Rencana Strategis Dinas Perhubungan DIY. Sementara itu kajian aspek manajemen risiko mencakup identifikasi, analisis dan mitigasi risiko. Hasil analisis menunjukkan bahwa dengan tersedianya jalur kereta api Parangtritis – Bandara YIA serta implementasi simpul-simpul alih moda transportasi, wisatawan dapat menggunakan moda transportasi umum menuju ke berbagai kawasan pariwisata di Kabupaten Kulon Progo, Bantul, dan Gunungkidul tanpa perlu menggunakan kendaraan pribadi. Selain itu, dengan adanya jalur kereta api Parangtritis – Bandara YIA memungkinkan angkutan barang dari pertambangan, pertanian, dan perikanan di Kulon Progo dan Bantul diangkut menggunakan kereta api menuju berbagai kota lain. Namun, untuk mewujudkan jalur kereta api Parangtritis – Bandara YIA perlu dilakukan pengendalian risiko aspek lahan, fluktuasi finansial, dan tingkat keterisian penumpang, serta mitigasi terhadap risiko desain, konstruksi, dan keselamatan, kesehatan kerja, dan lingkungan.

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)0.001
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 score0.048
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0320.005

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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