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Record W3128242802 · doi:10.37715/consortium.v2i1.3292

PENINGKATAN KOMPETENSI GURU EKONOMI (SMA,SMK DAN MA) DI KABUPATEN PACITAN “ UPDATE SAK-IFRS, SAK-ETAP, SAK-EMKM, SAK-SYARIAH DAN SAP”

2021· article· id· W3128242802 on OpenAlexaff
Wahidahwati Wahidahwati, Oyong Lisa, Maratus Zahro

Bibliographic record

VenueJournal Community Service Consortium · 2021
Typearticle
Languageid
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesArt

Abstract

fetched live from OpenAlex

Tujuan Pengabdian pada masyarakat ini memberikan tambangan pengetahuan tentang perkembangan Standar Akuntansi Keuangan yang digunakan di Indonesia pada guru akuntansi SMA,SMK dan MA yang ada di Kabupaten Pacitan. Selain itu juga memberikan wawasan pengetahuan tentang pentingnya meng-update Standart Akuntansi Keuangan tang ada di Indonesia untuk meningkatkan profesionalitas bagi guru Akuntansi di Kabupaten Pacitan. Sasaran pengabdian adalah guru-guru akuntansi SMA, SMK dan MA di Kabupaten Pacitan. Kegiatan pengabdian masyarakat dilakukan dalam tiga tahap kegiatan yaitu persiapan, pelaksanaan dan evaluasi. Persiapan dilakukan dengan melakukan survey pendahuluan yaitu melakukan observasi dilapangan mengenai pengetahuan guru-guru yang berhubungan dengan update 5 SAK di Indonesia. Pelaksanaan dilakukan dengan workshop menggunakan metode ceramah presentasi nara sumber dilanjutkan dengan diskusi tanya jawab sebagai bentuk peningkatan potensi pengetahuan guru. Hasil kegiatan pelatihan menunjukkan bahwa guru-guru Akuntansi Keuangan mendapatkan pemahaman yang lebih baik tentang 5 Standar Keuangan di Indonesia dan memperoleh sumber referensi mengenai SAK-IFRS, SAK-ETAP, SAK-EMKM, SAK-Syariah dan SAP, dan diharapkan guru-guru dapat meneruskan pengetahuan ini ke siswa-siswi dalam pembelajaran akuntansi keuangan. Selain update Standar akuntansi keuangan juga ada materi Metode Pembelajaran pada siswa Berbasis IT dan Peran Akuntansi di Era Industri 4.0. Pengabdian ini diharapkan berlanjut untuk materi selanjutnya mengenai penerapan lebih rinci dari masing-masing standar akuntansi keuangan.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0510.017

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 head0.100
GPT teacher head0.343
Teacher spread0.243 · 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
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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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