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Record W4285486278 · doi:10.56357/jt.v16i2.235

SISTEM INFORMASI PARIWISATA KABUPATEN KARANGANYAR BERBASIS WEBSITE

2021· article· id· W4285486278 on OpenAlexaff
Adnan Terry Suseno Genta Putra Dua

Bibliographic record

VenueTRANSFORMASI · 2021
Typearticle
Languageid
FieldComputer Science
TopicInformation Retrieval and Data Mining
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Sistem Informasi Pariwisata Kabupaten Karanganyar Berbasis Web digunakan sebagai alat bantu dalam penyampaian informasi kawasan wisata yang ada di Kabupaten Karanganyar kepada masyarakat yang ingin mengetahui daerah-daerah pariwisata yang ada di Karanganyar. Sistem Informasi Pariwisata Kabupaten Karanganyar Berbasis Website merupakan salah satu bentuk promosi pariwisata daerah yang ada di Kabupaten Karanganyar, agar menarik para wisatawan untuk berkunjung ke Kabupaten Karanganyar. Penelitian ini diharapkan dapat bermanfaat sebagai media informasi dan promosi potensi wisata yang ada di Kabupaten Karanganyar, sehingga masyarakat akan lebih mengenal tempat-tempat pariwisata daerah yang ada di Kabupaten Karanganyar. Semakin banyak wisatawan yang berkunjung maka pendapatan daerah dan masyarakat sekitarnya akan mengalami peningkatan. Metode penelitian yang dilakukan antara lain melalui observasi langsung, Studi Pustaka yang berhubungan dengan masalah yang diangkat. Sistem Informasi Pariwisata Kabupaten Karanganyar Berbasis Web dibuat dengan menggunakan WordPress dengan Bahasa PHP dengan database MYSQL. Kata kunci : Sistem Informasi Pariwisata Kabupaten Karanganyar Berbasis Website

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)0.001
metaresearch head score (Gemma)0.003
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: Software · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0090.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0840.044

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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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
GenreSoftware

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

Citations2
Published2021
Admission routes1
Has abstractyes

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Same venueTRANSFORMASISame topicInformation Retrieval and Data MiningFrench-language works237,207