SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN BANTUAN PROGRAM KELUARGA HARAPAN (PKH) DENGAN METODE ELECTRE (ELIMINATION ET CHOIX TRADUISTANT LA REALITE) STUDI KASUS: KECAMATAN SELESAI
Bibliographic record
Abstract
Program Keluarga Harapan (PKH) is an intense social protection program on providing cash assistance to households that meet the criteria of the Program Keluarga Harapan (PKH). The goal of Program Keluarga Harapan (PKH) in the short term is to reduce the burden of KSM (Very Poor Families) while in the long term it is expected to break the poverty chain between generations, so that the next generation can get out of poverty and be more prosperous. Based on the results of this study proposed a decision support system with the METHOD ELECTRE (Elimination Et Choix Traduisant La Realite) which is one of the multi-criterion decision making methods based on the concept of outranking by using a paired comparison of alternatives based on each appropriate criteria. From the ELECTRE method, there is an alternative result that is less favourable, namely A1 with the result of 0, A2 with the result of 0, A3 with the result of 2, A2 with the result of 1 and A5 with the result of 4. Thus the A5 becomes the alternative with the highest value.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".