MétaCan
Menu
Back to cohort
Record W4393123799 · doi:10.52186/aviasi.v20i1.130

Penerapan green airport dalam memberikan kepuasan kepada penumpang

2023· article· id· W4393123799 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAviasi Jurnal Ilmiah Kedirgantaraan · 2023
Typearticle
Languageid
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Artikel ini untuk mengisi kesenjangan dalam literatur dengan membuat perbedaan antara penelitian tentang green airport, dan passenger satisfaction, meskipun banyak dari variabel yang disebutkan di atas mungkin telah ditulis, makalah ini berupaya menambahkan dua variabel yang disebutkan di atas secara kolektif jika sudah ada pembahasannya, Metode yang digunakan dalam artikel ini ialah kualitatif dengan teknik grafis, disertai sumber tambahan, dengan mengumpulkan data yang diperlukan kemudian dianalisis dan klarifikasi dengan tepat, sebagai informasi tambahan digunakan dalam mencari data tambahan untuk penyelidikan, sumber berasal dari artikel ilmiah dari jurnal-jurnal reputasi nasional dan internasional, serta internet untuk mengumpulkan data tambahan. Hasil artikel ini menyatakan penerapan green airport dengan passenger satisfaction merupakan dua variabel yang telah ada dari beberapa hasil penelitian dengan dukungan artikel ilmiah yang sudah dijabarkan dalam hasil dan pembahasan, bandara di Indonesia sendiri sudah menerapkan green airport dengan adanya kebijakan nasional dan di dukung kebijakan internasional dari ICAO, passenger satisfaction dalam menggunakan bandara yang sudah menerapkan green airport sudah menikmati fasilitas yang di syaratkan dengan kebijakan dan fasilitas tambahan yang membuat passenger merasa puas dengan adanya pelayanan yang diberikan oleh bandara di Indonesia maupun di dunia. Implementation of the green airport in providing satisfaction to passengers Abstract: This article seeks to fill a gap in the literature by making a distinction between research on green airports and passenger satisfaction; although many of the variables mentioned above may have been written, this paper seeks to add the two variables mentioned above collectively if there is already a discussion, The method used in this article is qualitative with graphic techniques, accompanied by additional sources, by collecting the necessary data then analyzed and clarified appropriately, as additional information is used in finding additional data for investigation, sources come from scientific articles from journals of national and international reputation, and the internet to collect additional data. The results of this article state that the application of green airports with passenger satisfaction are two variables that have existed from several research results with the support of scientific articles that have been described in the results and discussion. Airports in Indonesia itself have implemented green airports with national policies and supported by international policies from ICAO, passenger satisfaction In using airports that have implemented green airports, they have enjoyed the facilities required by additional policies and facilities that make passengers feel satisfied with the services provided by airports in Indonesia and in the world.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.007

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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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