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Record W4407275010 · doi:10.47662/jaliye.v3i2.889

PERAN BISNIS DIGITAL, DESAIN, DAN TEKNOLOGI DI SMK BBC MEDAN

2024· article· en· W4407275010 on OpenAlexaff
Widi Sriwahyuni Pasaribu, Charini Aisyah, Taufik Yuandika, Denny Hartanto

Bibliographic record

VenueJALIYE Jurnal Abdimas Loyalitas dan Edukasi · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

One of the levels of education in Indonesia is Vocational High School (SMK), whose graduates are expected to be ready to work, especially to create job opportunities according to their vocational skills. Currently, a realistic step that graduates can take is to start a business by leveraging digital technology. Digital business is a transformation toward more efficient business practices. This activity aims to educate students about the role of digital business, design, and technology in entrepreneurship. The partners in this activity are students of SMK BBC Medan. The method used is Community Education as a substitution for science and technology. The material is delivered through lectures with the assistance of PowerPoint. The Community Service Program (PKM) activities include observation, implementation, documentation, and evaluation. The results of the PKM activity observation show that the students have an interest in starting a digital business. This is evident from the enthusiasm and curiosity of the students there.

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)0.001
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: Other
Teacher disagreement score0.047
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0470.020

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 head0.302
Teacher spread0.277 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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