Economic Valuation of Oil Palm Plantation Investment in Swamp Area of Tapin Regency, South Kalimantan, Indonesia
Bibliographic record
Abstract
This study describes the companies’ feasibility determination on oil palm plantation investment. We also compare it with the oil palm plantation in swamp area, by considering economic, social and environmental aspects. We used total valuation method to valuing the environmental value of swamp area. Otherwise, investment analyzed by the model of benefit cost ratio (BCR), net present value (NPV), and internal rate of return (IRR). The study showed that the financial valuation of investment feasibility that is made and proposed by the plantation companies to banks (creditors), did not account the land value (economic, social and environmental values) of swamp ecosystems. The assessment on swampland value obtained Rp232, 570,833,400 or US$24,481 million per year for 10,000 ha area – US$2,448 per ha each year. Although the total value of economic environment is included in the valuation element of oil palm plantation investment in swampland, it still result insufficient value. However, by sensitivity analysis scenario of swampland plantation would become sufficient if the Crude Palm Oil (CPO) price is above US$1300 per ton. It also has a second scenario if the environmental cost can be pressed optimally into Rp9, 025,541 or US$950 per ha per year.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".