Feasibility Investment Analysis on Development Telkom Landmark Tower Building at PT Telkom Landmark Tower
Bibliographic record
Abstract
PT Telekomunikasi Indonesian, Tbk (Telkom) intends for the consolidate entire operational activities Telkoms' office and subsidiaries which at this time some of them still rent office building to another party in Jakarta, to be united into one office building which will referred as Telkom Landmark Tower (TLT). To apply this program, the Board of Directors Telkom has assigned that the TLT will be built in land belonging to Telkom in Jalan Jendral Gatot Subroto, Jakarta. Property commercial industry, in particular office space on quarter IV-2012 in the Jabodebek experiencing positive development, it is indicated with increase in supply which followed with increase in occupancy rates and sales as well as tariff lease and price the selling. Based on the fact Telkom plans to build the building which can accommodate the needs office space for Telkom Group, hence it can decrease rent expense office buildings in Group. In conduct of feasibility investment analysis on the construction of TLT using capital budgeting method, with some approaches namely Payback Period, Net Present Value, Internal Rate of Return and Profitability Index. Based on the results of calculation and feasibility investment analysis using capital budgeting method obtained the result that the investment of the construction of TLT feasible to be implemented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".