Analisa Pemilihan Mesin Pendorong Pokok Kri Clurit-641 dalam Melaksanakan Re Engine Untuk Mendukung Operasi di Wilayah Koarmada I
Bibliographic record
Abstract
KRI Clurit-641 is one of the naval defense assets of the Indonesian Navy operating under the jurisdiction of Koarmada I and holds a strategic role in maintaining maritime security stability. However, due to aging components and the high intensity of operational deployment, the vessel has encountered several technical issues, including decreased engine performance, increasing frequency of propulsion system failures, limited availability of spare parts, and rising maintenance costs. These challenges necessitate the implementation of a re engine program to ensure optimal operational readiness. This study aims to identify the main criteria and sub-criteria for selecting a replacement propulsion engine, determine the most suitable engine alternative, and formulate a supporting strategy based on internal and external conditions. The Analytical Hierarchy Process (AHP) method is applied to evaluate the priority of each criterion and determine the best alternative, while SWOT analysis is used to develop an appropriate implementation strategy. The research findings indicate that the Technical Requirement criterion, particularly the reliability sub-criterion, holds the highest weight at 35.4%, while the Operational Requirement criterion with the strategic sub-criterion follows with a weight of 33.2%. Among the three engine alternatives analyzed, the MTU 12V 2000 M93 emerged as the most suitable choice with a total weight of 36.3%. A diversification strategy is recommended, based on the SWOT position that reflects internal weaknesses but significant external opportunities. Therefore, the re-engine of KRI Clurit should be conducted by aligning technical and strategic considerations with defense policy direction to support sustainable and efficient operations
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".