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Record W4392064645 · doi:10.51826/fokus.v19i2.558

PENINGKATAN KOMPETENSI SUMBER DAYA MANUSIA DALAM PENGEMBANGAN SEKTOR PARIWISATA

2022· article· id· W4392064645 on OpenAlex
A.M. YADISAR

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFOKUS Publikasi Ilmiah untuk Mahasiswa Staf Pengajar dan Alumni Universitas Kapuas Sintang · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsBusinessBusiness administrationEnvironmental science

Abstract

fetched live from OpenAlex

Salah satu aspek penting dalam mengembangkan pertumbuhan sector pariwisata adalahketersediaan aparatur. Pemerintah Kabupaten Sintang dalam hal ini Dinas Pemuda, Olah Raga danPariwisata menghadapi kendala minimnya ketersediaan apataur yang mempunyai kemampuan yangmemadai dalam mengembangkan potensi kepariwisataan yang ada. Rancangan penelititian yangdigunakan adalah penelitian deskriftif kualitatif, Sumber data dalam penelitian ini adalah Kepala DinasPemuda, Olah Raga dan Pariwisata Kabupaten Sintang, Kepala Bidang Pariwisata Dinas Pemuda,Olah Raga dan Pariwisata Kabupaten Sintang, Aparatur di Dinas Pemuda, Olah Raga dan PariwisataKabupaten Sintang. Dilihat dari aspek kompetensi pimpinan diketahui bahwa kemampuan pemikiranstrategis, kemampuan menghadapi berbagai perubahan yang terjadi serta kemampuan manajemenhubungan yang dimiliki belum mempunyai motivasi yang tinggi untuk memenangkan persaingan melaluipenemuan jasa-jasa, produk dan proses produksi yang baru. Upaya peningkatan kompetensi aparaturseperti pendidikan dan latihan yang berhubungan dengan sector kepariwisataan sudah cukup baikwalaupun masih belum optimal dilakukan hal ini disebabkan dampak dari pamdemi Covid-19. Faktorinternal yang mempengaruhi peningkatan kompetensi aparatur, yaitu ketersediaan dana, sikap pimpinan,motivasi pegawai serta ketersediaan sarana dan prasarana pendukung.

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.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.005
Science and technology studies0.0150.002
Scholarly communication0.0020.003
Open science0.0060.007
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0190.000

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 head0.018
GPT teacher head0.245
Teacher spread0.227 · 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