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Pembuatan Peta Sebaran Destinasi Wisata di Desa Wisata Angsana, Desa Setu, kecamatan Jasinga.

2023· article· id· W4388244793 on OpenAlexaff
Helmi Hermawan, Budi Setiawan

Bibliographic record

VenueIKRA-ITH ABDIMAS · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Desa Setu, Kecamatan Jasinga mempunyai program kerja jangka panjang. dimanaprogram ini bertujuan untuk mengembangkan Desa Wisata yang ada di Kecamatan Jasingadengan nama Desa Wisata Angsana. Sebelum melaksanakan program kerja, mahasiswa dalamkegiatan pengabdian kepada masyarakat (Pkm) yang berjumlah 22 orang dibagi menjadi 5program studi di beberapa titik. Pertemuan dengan Pengurus Dewi Angsana beserta Bu Kadespada Tanggal 5 Juli 2023 mengenai perencanaan proker dalam kegiatan pengabdian kepadamasyarakat (Pkm) dari tiap prodi yang akan dilaksanakan kick off tgl 11 Juli 2023. Dari prodiperencanaan wilayah kota sendiri akan membuat sebuah peta denah lokasi desa wisataAngsana dengan tahapan awal melakukan sosialisasi kepada masyarakat untuk mendapatkaninformasi,melakukan survei terhadap lokasi wisata untuk mengetahui titik-titik wisata danmelakukan pemetaan, yang bertujuan untuk mempermudah pariwisata untuk mengetahui lokasidesa wisata Angsana itu sendiri. Dikarenakan desa wisata Angsana ini masih tergolong desawisata perintis maka dari itu masih diperlukan suatu ranah perkenalan seperti memberi tahulokasi desa wisata ini agar dapat membantu menemukan arah jalan atau aksesibel yang mudahuntuk menuju lokasi desa wisata angsana yang berada di desa Setu. Kemudian programselanjutnya dari perencanaan wilayah dan kota akan membuat peta sebaran wisata pada desawisata Angsana agar memberi tahu keunggulan serta membantu para turis atau wisatawanmenemukan lokasi wisata yang tersebar pada desa wisata angsana itu sendiri.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.038
GPT teacher head0.311
Teacher spread0.273 · 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 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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