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Record W3008872110 · doi:10.22334/jihm.v10i1.161

PERBANDINGAN NILAI BUDAYA KARYAWAN HOTEL DI SEMINYAK DAN UBUD

2019· article· en· W3008872110 on OpenAlexaff
Made Arya Astina, Anak Agung Gede Wijaya

Bibliographic record

VenueJurnal Ilmiah Hospitality Management · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTourismDestinationsHuman resourcesBusinessMarketingBusiness administrationGeographyManagement

Abstract

fetched live from OpenAlex

The research on this tourism human resource is titled Comparison of Employee Culture value hotels in Seminyak and Ubud. This research is a quantitative study conducted in two tourist destinations in Bali namely Seminyak and Ubud area. Data collection techniques are carried out by distribution of polls, and literature studies. The research period will be held in August 2019 – October 2019. As for the research subject specified is a number of each of the 60 employees of the hotel in both areas. Seminyak and Ubud area were chosen as the location of the research with several considerations: 1) Seminyak and Ubud are the main tourist destinations in Bali, 2) The growth of the number of hotels in both regions is equally fast, 3) the culture owned by hotel employees In Seminyak and Ubud need to be analyzed for product development (service). The theory used in the study was the cultural value theory of Hofstede. Angket (questionnaire) used to refer to VSM (Value Survey Mudule) developed by Hofstede. Since the province of Bali relies on the tourism sector for its region's major income, the research is important because human resources are an important component of the service. This research resulted in several findings on the similarities and differences in the value of hotel employees ' culture in Seminyak and Ubud areas.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.008
GPT teacher head0.269
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; a candidate call from one teacher head, not a consensus.

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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