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Record W2461406148 · doi:10.5539/emr.v5n2p8

Model of Integrated Vocational School (SMK) Products in Gresik Regency

2016· article· en· W2461406148 on OpenAlexvenueno aff
Mochammad Nuruddin, Rahmat Agus Santoso

Bibliographic record

VenueEngineering Management Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicVocational and Entrepreneurial Education
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationEngineeringProduct (mathematics)SWOT analysisAutomotive industryEngineering managementIdentification (biology)Consolidation (business)Manufacturing engineeringMarketingBusinessMathematicsPsychologyPedagogy

Abstract

fetched live from OpenAlex

The main goal of this study is to do needs and potential analysis of products in each vocational school in Gresik regency that is expected to create products integration based on the excellence of vocational secondary schools, thus it is necessary to sustain ably design an identification concept of potency and integration model. By using the design of Research and Development some necessary steps taken into account: a) identification of vocational high schools (SMK), b) SWOT analysis, c) cluster analysis, d) mapping of vocational high schools (SMK). The second stage (consolidation and integration), consists of the following activities: a) vocational high schools (SMK) grouping, b) designing a model of integration, c) conducting consolidation among related parties, d) implementing synergistic product integration. The results of the identification of Vocational High School (SMK) potency in Gresik based on the clusters that are formed in the effort of realizing a model design of integration products in Vocational High School (SMK) which refers to the spectrum of field, program and science package, hence two kinds of alternative product integration, namely 1) The product integration of Technology and Engineering field spectrum, Automotive Engineering program and Light Vehicle Engineering science package. 2) Product integration of the spectrum of Information and Communication Technology science field, Computer Engineering and Informatics science program and Computer Engineering and Network science package, so that the integration model of product which is formed needs synergetic a pattern of integration by the (3) related parties in order to produce excellent local product of Gresik regency, the synergetic integration model pattern will run optimally when each party has a high commitment to the creation of local superior products generated by Vocational High School in Gresik regency in order to face the era of global markets which can be realized through the integration of Vocational High School products.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.104
GPT teacher head0.369
Teacher spread0.265 · 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 designSimulation or modeling
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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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