SISTEM PENDUKUNG KEPUTUSAN DALAM MENENTUKAN HAKIM TERBAIK PADA PENGADILAN AGAMA KELAS 1A MEDAN MENERAPKAN METODE ANALYTICAL HIERARCY PROCESS (AHP) DAN PROMETHEE II
Bibliographic record
Abstract
Medan Religious Court Office Class 1 A located on Jalan Sisingamangaraja KM 8.8 as a place that organizes law enforcement and justice at the first level for people seeking justice for certain cases among people who are Muslim in the fields of marriage, inheritance, will, grant, endowment, zakat, infaq, shadaqah and sharia economics. In the Medan Class 1A Religious Courts Office there are a number of positions that are chaired, and there are several judges who are tasked with providing justice to settle cases handled. Medan Class 1 A Religious Court Office provides a reward or award with the aim of improving the performance of Judges on duty, and to determine the best Judges, alternatives and criteria are needed to be a reference in the selection process. Decision Support System is one method that can be used in the process of selecting the best Judges. In this study, the authors used the Analyticalcal Hierarchy Process (AHP) method to find the weighting value of the criteria, and the Promethee II method to find the final grade or to find the best Judge's ranking. Thus the Decision Support System is needed in order to help the Medan Religious Court Office to determine the best Judge.Keywords: Decision Support System, AHP, Promethee II, Selection of the Best Judges
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".