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Record W4391004417 · doi:10.37277/stch.v33i4.1750

Etnik Nusantara Modern Terminal Bus Tipe A Cijulang Pangandaran

2023· article· en· W4391004417 on OpenAlexaff
Muflihul Iman, Maulana Dian P, Egga Ryandona

Bibliographic record

VenueSainstech Jurnal Penelitian dan Pengkajian Sains dan Teknologi · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsTourismGovernment (linguistics)DestinationsEthnic groupBusinessTransport engineeringGeographyEngineeringPolitical scienceLaw

Abstract

fetched live from OpenAlex

ABSTRACT West Java is one of the regions in Indonesia with a variety of extraordinary tourist destinations. The attraction of destinations in West Java can invite local and international tourists to come to visit. Pangandaran is one of the regencies in West Java Province. The area of Pangandaran Regency is 168,509 hectares, with the greatest potential of Pangandaran Regency is tourism both beach and river attractions. Seeing the number of tourist attractions in Pangandaran Regency, the number of tourists reached 3.6 million tourist visits to tourist attractions in Pangandaran. The large number of private vehicle users that cause congestion is caused by inadequate infrastructure facilities in Pangandaran Regency such as public transportation, namely bus transportation. Currently, the terminal facilities owned by the Pangandaran Regency government only have 3 terminals with the condition of the bus terminal is very worrying, not managed properly, does not facilitate to existing tourist areas, and there are no terminal facilities that function to serve intercity transportation between provinces (AKAP). Therefore, Cijulang Pangandaran Type A Bus Terminal presents a Modern Ethnic Nusantara concept to introduce and preserve the Ethnic Nusantara in West Java. Keywords : Bus Terminal, Cijulang Pangandaran, Ethnic Nusantara Modern

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.310
Teacher spread0.279 · 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 designOther design
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueSainstech Jurnal Penelitian dan Pengkajian Sains dan TeknologiSame topicCommunity-based Tourism Development and SustainabilityFrench-language works237,207