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Arahan Pengembangan Objek Wisata Huluwa Beach Di Negeri Wakasihu Kecamatan Leihitu Barat

2023· article· id· W4389030801 on OpenAlexaff
Elda Risna Pelu, Stevianus Titaley, Richard A. de Fretes

Bibliographic record

VenueJurnal ISOMETRI · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesArt

Abstract

fetched live from OpenAlex

Posisi sektor pariwisata Pantai Huluwa yang terletak di Negeri Wakasihu yang dikembangkan dari tahun 2016 menjadi objek daya tarik wisata di Provinsi Maluku. Pantai ini memiliki pesona pantai yang indah dengan banyak vegetasi yang berada di pinggir pantai yang bisa dinikmati para pengunjung, deretan batuan karang dan hamparan pasir putih juga ikut ambil bagian dari keindahan Pantai Huluwa. Dalam upaya untuk mencapai tujuan dari penelitian ini maka digunakan metode deskriptif kualitatif yaitu analisis potensi daya tarik wisata kemudian merumuskan rencana kawasan Obyek wisata Pantai Huluwa sesuai dengan karakteristik fisik dan daya tariknya. berdasarkan perhitungan daya dukung kawasan wisata yakni 1.000 orang dengan luas wilayah 20.550 m2 diketahui bahwa jumlah pengunjung belum memenuhi kapasitas daya dukung Pantai Huluwa. Perlu adanya prioritas perbaikan dan penambahan fasilitas pendukung kegiatan wisata. Berdasarkan hasil penelitian maka dapat direkomendasikan bahwa perlu adanya melakukan penataan terhadap fasilitas penunjang aktivitas wisata yang telah rusak dan juga perlu adanya penggadaan fasilitas yang diperlukan oleh para pengunjung untuk memenuhi kebutuhan kegiatan wisata pada Pantai Huluwa harus terus mengembangkan ide wisata yang menarik serta tetap harus memprioritaskan kebutuhan para pengunjung.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.006

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 head0.035
GPT teacher head0.311
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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