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Record W4412906154 · doi:10.52352/jastd.v1i2.1216

Dampak Motivasi Simbolis Kunjungan Wisatawan ke Destinasi Pariwisata Berbasis Ekowisata

2024· article· id· W4412906154 on OpenAlexaff
Jery Christianto, Bergas Anggito Adjie, Irma Dela Larasita, Alhilal Furqan, Kiki Priscilia, M. Asfahani Sauky

Bibliographic record

VenueJournal of Applied Science in Tourism Destination · 2024
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessComputer science

Abstract

fetched live from OpenAlex

Popularitas ekowisata di kalangan wisatawan mancanegara maupun domestik kian meningkat di Indonesia. Unggahan konten ekowisata di sosial media dapat mempengaruhi keputusan pengunjung dan memberikan perasaan puas bagi pengunggah. Pengakuan melalui sosial media atau motivasi simbolis menjadi salah satu motivasi wisatawan untuk mengunjungi ekowisata. Jumlah wisatawan dengan motivasi simbolis semakin banyak, sejajar dengan meningkatnya penggunaan sosial media secara global, yang dapat berdampak pada perkembangan ekowisata, Penelitian ini mengidentifikasi faktor wisatawan dengan motivasi simbolis ingin mengunjungi tiga taman nasional (TNGL dan TN Komodo) di Indonesia dan dampak yang ditimbulkan dari fenomena ini. Penelitian ini adalah penelitian kualitatif, dengan data didapatkan melalui studi kepustakaan dan dianalisis secara deskriptif. Penelitian ini mendapatkan bahwa faktor wisatawan dengan motivasi simbolis mengunjungi dua lokasi tersebut yaitu pemandangan indah dan terdapat spot foto, gaya hidup berbeda yang ditawarkan destinasi, relaksasi, adanya nilai eksklusifitas, dan keinginan sensation seeking ke tempat wisata yang tren di sosial media karena banyak ulasan positif. Fenomena ini berdampak positif juga negatif dalam aspek lingkungan, ekonomi, dan sosial budaya pada dua taman nasional ini.

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)0.023
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0000.002
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 head0.020
GPT teacher head0.305
Teacher spread0.286 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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