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Record W3013620287 · doi:10.37695/pkmcsr.v2i0.597

Pelatihan Kewirausahaan Melalui Pembuatan Produk Kue Bagi Guru Kewirausahaan SMK Se-Jakarta Selatan

2019· article· id· W3013620287 on OpenAlexaff
Rahmat Kusnedi

Bibliographic record

VenueProsiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) · 2019
Typearticle
Languageid
FieldSocial Sciences
TopicVocational and Entrepreneurial Education
Canadian institutionsCenterLine (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Ketersediaan tenaga kerja terampil yaitu lulusan sekolah menengah seperti SMK sangat dibutuhkan untuk operasional sejumlah infrastruktur yang akan dibangun pemerintah tetapi pada kenyataannya hasil lulusan SMK tidak mempunyai kapabilitas dan kompetensi yang sesuai dengan kebutuhan. Kekurangan kompetisi siswa siswi SMK ini juga didapat dari kurangnya kompetensi yang dimiliki oleh guru sebagai tenaga pengajar, Hampir 80 persen dari guru SMK merupakan guru normatif yang mengampu pelajaran Bahasa Indonesia, Inggris, Agama dan PKN sehingga hanya enam persen output pendidikan nasional yang mampu bersaing secara global. Salah satu mata pelajaran yang kompetisi gurunya kurang dalam hal praktek adalah mata pelajaran kewirausahaan dan menyebabkan siswa hanya menerima pembelajaran dalam bentuk teori saja, hal ini memicu program studi seni kuliner Pradita Institute untuk memberikan pelatihan kepada guru SMK kewirausahaan, pelatihan dalam bentuk PkM dilakukan bekerjasama dengan Musyawarah Guru Mata Pelajaran Kewirausahaan se-Jakarta Selatan. Kegiatan PkM dirancang dengan metode pengajaran singkat dan praktek, praktek pelatihan difokuskan pada pelatihan pembuatan produk kue.
 Pelaksanaan Kegiatan PkM berlangsung di Gedung B Pradita Institute, Pelatihan pembuatan produk kue diantaranya; chocolate chips, onde-onde, swiss roll dan talam ubi. Diharapkan melalui PkM ini para guru-guru mampu menambah kompetensi dan mengajarkan kembali kepada siswa siswi nya. Kegiatan PkM ini juga mampu memacu semangat mereka untuk menjadi seorang wirausahawan dan berguna bagi perekonomian mitra.

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)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.004
Science and technology studies0.0060.002
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.004

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 head0.091
GPT teacher head0.320
Teacher spread0.229 · 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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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