The implementation of BORDA and PROMETHEE for decision making of Naval base selection
Bibliographic record
Abstract
The objective of this research is to determine the location for the dock and office of naval bases in Padang city of Indonesia. Following this objective, the Regional Government of Padang Mentawai Islands District provides 3 (three) alternative places namely in Semabuk Bay, Siuban Bay, and Semebai Bay for the location of dock and office of Naval Base. For the selection of Mentawai base, the method uses BORDA and PROMETHEE, since the methods can consider alternative evaluation based on factors that are both qualitative and quantitative. Based on the research of BORDA method calculation on 16 naval base selection criteria, it is found that criterion of Sailing Flow maintains the highest weight value that is equal to 10.9% and the lowest criterion weighted value belongs to criterion Political Condition for about 2%. For the results of ranking against the alternative using the Promethee method, the study obtains Semebai Bay as the best location to serve for the location of the base of the Mentawai Naval Base.
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.
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 | 0.052 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".