INVESTMENT FEASIBILITY STUDY OF PT HARDAYA MINING ENERGY SEBAKIS ON SITE COAL LABORATORY IN 2022
Bibliographic record
Abstract
PT Hardaya Mining Energy (PT HME) as a coal supplier in Indonesia with a quantity of 3 million Metric Tons (MT) per year is still testing coal samples by sending a large number of samples per day to PT Sucofindo Tarakan Branch and also other PT Sucofindo Branches in the Kalimantan region which costs a lot of additional shipping costs and makes the certificate issuance time long, so PT HME plans to work with PT Sucofindo Tarakan Branch to procure PT HME On Site coal laboratory. The purpose of this study is to assess the financial feasibility of PT HME's On Site laboratory procurement investment. Quantitative descriptive research method is used in this research to find the amount of investment feasibility value based on the Net Present Value (NPV), Internal Rate of Return (IRR), Payback Ratio (PP), and Break Event Point (BEP) formulas. The results of this study show an NPV value greater than zero, the IRR value is at a percentage of 55%, PP produces a value of 0.81 years or 9.76 months, and has a BEP value that increases every year. Thus, PT HME's on-site coal laboratory investment is feasible.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".