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Record W4403238478 · doi:10.29313/bcsurp.v4i3.14011

Identifikasi Potensi Eduwisata Perlebahan Gunung Guntur

2024· article· en· W4403238478 on OpenAlexaff
Savella Deanova Supatno, Astri Mutia Ekasari, Riswandha Risang Aji

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

Abstract. Gunung Guntur has great potential to be developed as a tourism destination, including beekeeping edu-tourism, considering the biodiversity and natural conditions that support sustainable beekeeping.. This study aims to identify the potential of Gunung Guntur Beekeeping Edu-tourism through an in-depth analysis of tourism aspects: attraction, amenities, accessibility, and ancillary. The research method used is a mixed-method approach, combining quantitative and qualitative methods to provide a comprehensive overview. Data were collected through purposive sampling techniques involving 6 respondents, as the sample selection was based on data relevance and specific criteria. The research results indicate that the attraction aspect is very high, accessibility and ancillary aspects are high, and the amenities aspect requires optimization to enhance competitiveness, attract more visitors, and promote sustainability as well as local economic growth. Beekeeping Edu-tourism has great potential because it combines elements of tourism and education, offering an educational and recreational experience about bee ecology and nature conservation. However, to achieve its maximum potential, improvements and sustainable management of facilities are needed to attract more visitors and contribute to environmental conservation and local economic empowerment. This underscores the importance of identifying tourism potential by focusing on the improvement and development of supporting facilities through proper management, thus potentially becoming a leading tourism destination that not only offers recreational experiences but also deep education with contributions to environmental conservation. Abstrak. Gunung Guntur memiliki potensi besar untuk dikembangkan sebagai destinasi wisata salah satunya eduwisata perlebahan, mengingat keanekaragaman hayati dan kondisi alam yang mendukung budidaya lebah yang berkelanjutan. Penelitian ini bertujuan untuk mengidentifikasi potensi Eduwisata Perlebahan Gunung Guntur melalui analisis mendalam terhadap aspek pariwisata: attraction, amenities, accessibility, dan ancillary. Metode penelitian yang digunakan adalah pendekatan campuran (mixed method), menggabungkan kuantitatif dan kualitatif untuk memberikan gambaran yang komprehensif. Data dikumpulkan melalui teknik purposive sampling dengan melibatkan 6 responden karena pengambilan sample sesuai relevansi data dan berdasarkan kriteria khusus. Hasil penelitian menunjukkan bahwa. Aspek attraction sangat tinggi, Accessibility dan ancillary tinggi, serta aspek amenities. Namun secara keseluruhan masih perlunya dioptimalkan untuk meningkatkan daya saing, menarik lebih banyak pengunjung, dan mendorong keberlanjutan serta pertumbuhan ekonomi lokal. Eduwisata Perlebahan memiliki potensi besar karena menggabungkan unsur wisata dan pendidikan, dengan daya tarik yang menawarkan pengalaman edukatif dan rekreasi tentang ekologi perlebahan serta pelestarian alam. Namun, untuk mencapai potensi maksimalnya diperlukan peningkatan dan pengelolaan fasilitas berkelanjutan agar dapat menarik lebih banyak pengunjung dan berkontribusi pada pelestarian lingkungan serta pemberdayaan ekonomi lokal. Sehingga ini menegaskan pentingnya mengidentifikasi potensi wisata dengan memperhatikan peningkatan dan pengembangan fasilitas pendukung melalui pengelolaan yang tepat, sehingga berpotensi menjadi tujuan wisata unggulan yang tidak hanya menawarkan pengalaman rekreasi tetapi juga pendidikan yang mendalam dengan kontribusi pelestarian lingkungan.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.226
Teacher spread0.202 · 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 designNot applicable
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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