ANALISIS COST VOLUME PROFIT SEBAGAI DASAR PERENCANAAN LABA PERUSAHAAN YANG DIHARAPKAN (STUDI KASUS SULTAN’S BARBERSHOP)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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 it