Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.164 | 0.032 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".