ANALISIS COST VOLUME PROFIT SEBAGAI DASAR PERENCANAAN LABA PERUSAHAAN YANG DIHARAPKAN (STUDI KASUS SULTAN’S BARBERSHOP)
Bibliographic record
Abstract
A company needs planning to assist management in estimating the level of profit to be obtained, with a Cost-Volume-Profit analysis that focuses on various factors that influence changes in the earnings component. This study aims to determine the application of CVP analysis as a basis for expected earnings planning for the second quarter of 2020. The method used is a descriptive method with a case study approach. Researchers gather company information and then conduct data analysis. CVP analysis is performed with break event point (BEP) analysis, contribution margin, and margin of safety. The results showed that in the first quarter the contribution margin was IDR 32,424,125. The minimum sales are IDR 19,330,018 and the break-even point is IDR 39,838,182. The company set a profit of 20% from the first quarter. To achieve the expected profit, sales are targeted at Rp. 62,775,909 in the second quarter. Management can apply CVP analysis to assist in planning earnings in the following quarter.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".