Financial Performance Analysis and Valuation Assessment of Pt Bumi Resources in Comparison with Pt. Adaro Energy Tbk. and Pt. Bukit Asam Tbk. For Period of 2017-3rd Quarter of 2022
Bibliographic record
Abstract
Indonesia is the third largest country in the world producing coal products. PT. Bumi Resource Tbk. (BUMI) is a coal industry company with the highest market capital, but its financial performance is not good when viewed from its net income in the 2017-3rd quarter of 2022. Financial ratio analysis is used to evaluate the company’s financial performance. This analysis uses the provisions of the ministry No.KEP-100/MBU/2002 which is divided into 4 factors, namely profitability, liquidity, activity and solvency ratio. Economic Value Added (EVA) and FCFF valuation are the methods used in this research. For external analysis, researchers use PEST analysis. The researcher found that BUMI’s financial performance was categorized as an unhealthy company based on its financial ratio analysis with an average rating of B. Based on the EVA method, BUMI’s financial performance was considered not good considering that its value was always negative. From the FCFF valuation, the Intrinsic Value of BUMI is IDR 250.29 when the current price is IDR 147. So, the BUMI company is concluded to be undervalued.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".