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Record W3176162721 · doi:10.32534/jpk.v4i1.790

PENGARUH SISTEM INFORMASI AKUNTASI DALAM MENDUKUNG PELAKSANAAN PENGENDALIAN INTERN PEMBELIAN DAN PENGELUARAN KAS CV. AIDA ROTAN CIREBON

2017· article· id· W3176162721 on OpenAlexaboutno aff
Yoga Satria Nugraha, Itat Tatmimah

Bibliographic record

VenueJurnal Proaksi · 2017
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesArt

Abstract

fetched live from OpenAlex

ABSTRAK
 Permasalahan dalam penelitian ini adalah perlu adanya Sistem Pengendalian Intern untuk mengamankan harta maupun pendapatan serta memberikan keyakinan tentang kebenaran yang dapat dipercaya agar dapat mendorong adanya efisiensi usaha dengan monitor terus menerus apakah kebijakan yang ditetapkan sebelumnya telah dilaksanakan sebagaimana mestinya.Sistem Informasi Akuntansi Pembelian dan Pengeluaran Kas diciptakan dengan tujuan untuk membantu pihak manajemen tentang kegiatan usaha, terutama kegiatan Pembelian dan Pengeluaran Kas yang dikelolanya dan pihak luar yang berkepentingan terhadap perusahaan. CV. Aida Rattan adalah salah satu perusahaan yang memproduksi kerajinan rotan antara lain berbagai macam model kursi yang terbuat dari rotan, meja dan perabotan rumah tangga yang terbuat dari rotan, hasil produksinya dipasarkan di pasar domestic dan di ekspor ke Negara Eropa, Afrika selatan, Canada, Amerika Serikat, Jepang dan Australia. Hasil dari penelitian ini dilakukan melalui angket kepada 30 Responden yang dijadikan sampel penelitian dan pengolahan data menggunakan analisis data statistik dengan metode analisis regresi linier sederhana dan berganda. Kesimpulan dari penelitian ini adalah Sistem Informasi Akuntansi tidak bepengaruh signifikan terhadap Pengendalian Internal Pembelian dan Pengeluaran Kas.
 
 Kata Kunci : Sistem Informasi Akuntansi, Pengendalian Intern Pembelian dan Pengeluaran Kas

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.529
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0060.004
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.305
Teacher spread0.266 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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