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Record W4412730179 · doi:10.26905/jpp.v10i1.14518

Border tourism behavior in increasing the number of tourist visits in Batam

2025· article· en· W4412730179 on OpenAlexaff
I Wayan Thariqy Kawakibi Pristiwasa, Kanzila Eka Octavia

Bibliographic record

VenueJurnal Pariwisata Pesona · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTourismBusinessGeography

Abstract

fetched live from OpenAlex

Batam City is one of Indonesia's border areas that has great potential as a cross-country tourist destination. This study aims to analyze the behavior of cross-border tourists visiting Batam City, Indonesia, primarily from Singapore and Malaysia. The research focuses on four main variables: motivation, perceived quality, perceived risk, and tourist attitudes. The study employed a quantitative method by distributing questionnaires to 250 respondents across five main entry points: Batam Center Port, Harbour Bay, Sekupang, Waterfront City, and Nongsapura. Data analysis was conducted using cross-tabulation and chi-square tests. The findings revealed that prestige motivation, perceived price quality, health risks, and responsible attitudes were the dominant factors influencing tourist behavior. The implications suggest that local governments and tourism stakeholders should improve service quality and tourism products to enhance Batam’s competitiveness as a safe and attractive cross-border destination.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.360
Teacher spread0.347 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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