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Record W4401146404 · doi:10.32493/jiaup.v11i1.20940

Pengaruh Tata Kelola Perusahaan dan Kecakapan Manajerial terhadap Kualitas Laba

2023· article· en· W4401146404 on OpenAlexaff
Thariq Fadillah, Azas Mabrur

Bibliographic record

VenueJURNAL ILMIAH AKUNTANSI UNIVERSITAS PAMULANG · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsBusinessBusiness administration

Abstract

fetched live from OpenAlex

Abstract This study examines the effect of corporate governance mechanisms and managerial ability on earnings quality. There are three components of corporate governance discussed in this study, namely institutional ownership, independent board of commissioners, and audit committee. Earnings quality in this study is measured based on the value of discretionary accruals which indicate earnings management in the company. The research data is in the form of manufacturing companies listed on the IDX during the 2017-2019 period. Sample selection using purposive sampling method, obtained 105 samples so that the number of observations for 3 years becomes 315 observations. The analytical method used in this study is multiple linear regression panel data. The results of this study indicate that the independent board of commissioners has a positive effect on earnings quality, while institutional ownership and managerial ability have a negative effect on earnings quality. Meanwhile, the audit committee has no effect on earnings quality. Abstrak Penelitian ini menguji pengaruh mekanisme tata kelola perusahaan dan kemampuan manajerial terhadap kualitas laba. Terdapat tiga komponen tata kelola perusahaan yang dibahas dalam penelitian ini, yaitu kepemilikan institusional, dewan komisaris independen, dan komite audit. Kualitas laba dalam penelitian ini diukur berdasarkan nilai akrual diskresioner yang mengindikasikan terjadinya manajemen laba pada perusahaan. Data penelitian berupa perusahaan manufaktur yang terdaftar di BEI selama periode 2017-2019. Pemilihan sampel menggunakan metode purposive sampling, diperoleh 105 sampel sehingga jumlah observasi selama 3 tahun menjadi 315 observasi. Metode analisis yang digunakan dalam penelitian ini adalah data panel regresi linier berganda. Hasil penelitian ini menunjukkan bahwa dewan komisaris independen berpengaruh positif terhadap kualitas laba, sedangkan kepemilikan institusional dan kemampuan manajerial berpengaruh negatif terhadap kualitas laba. Sedangkan komite audit tidak berpengaruh terhadap kualitas laba.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.208
Teacher spread0.188 · 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 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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