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Record W2954475545 · doi:10.29244/fagb.7.2.121-142

FAKTOR-FAKTOR PENENTU KINERJA KEUANGAN USAHA AYAM BROILER DI KOTA KENDARI

2017· article· en· W2954475545 on OpenAlexaff
Normal Bivariant Padangaran, Dwi Rachmina, Anna Fariyanti

Bibliographic record

VenueForum Agribisnis · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock Farming and Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessProfitability indexAgricultural scienceCurrent ratioProduction (economics)Net incomeProfit (economics)AgriculturePath analysis (statistics)General partnershipFinanceAgricultural economicsEconomicsMathematicsStatistics

Abstract

fetched live from OpenAlex

Financial performance is one of measure to determine the condition of a business. The objectives of this research are: (1) to analyze the financial performance of broiler business in Kendari City; and (2) to analyze determinant factors of financial performance of broiler business in Kendari City. Research method uses financial ratio analysis and path analysis. The research was conducted in Kendari City with 72 respondents. The results of the research showed that: (1) number of chickens average 3.849 tails, were managed by partnership method and 8 times production in a year; (2) financial performance of broiler business are profitable; (3) number of production positive influenced by number of Day Old Chicken (DOC), number of labor, wide of cage, and experience on farming ; (4) the influence factor of current ratio, total assets turn over ratio, and profitability are number of production, equity ratio, and experience on farming. Based on the research results, then recomendate to: (1) farmers need to increase the production capacity of each production cycle or expanding businesses to use assets more efficiently and the income generated is also greater; (2) therefore the financial performance of broiler business was positively affected by the number of production, equity ratio, and experience on farming, to be able to increase operating profit and financial performance of the business it is suggested that these three things improved.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
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
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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
Published2017
Admission routes1
Has abstractyes

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