Penerapan Sistem Pendukung Keputusan Dengan Metode Fuzzy AHP Untuk Penentuan Kriteria Prioritas Pelayanan Dikementrian Agama Kota Binjai
Bibliographic record
Abstract
Penelitian ini bertujuan untuk menerapkan Sistem Pendukung Keputusan (SPK) dengan metode Fuzzy Analytical Hierarchy Process (F-AHP) untuk menentukan prioritas pelayanan di Kementerian Agama Kota Binjai. Metode F-AHP digunakan untuk mengatasi ketidakpastian dan subjektivitas dalam pengambilan keputusan multi-kriteria. Kriteria yang digunakan meliputi: Tingkat Kebutuhan Masyarakat, Dampak Sosial, Aksesibilitas Pelayanan, Kesiapan Sumber Daya, dan Dukungan Kebijakan/Regulasi. Hasil penelitian menunjukkan bahwa Tingkat Kebutuhan Masyarakat merupakan kriteria paling dominan dengan bobot 1,0. Dari sepuluh alternatif pelayanan, Fasilitasi Perayaan Hari Besar Agama Non-Muslim dan Penyusunan Kurikulum Pendidikan Agama Non-Muslim di Sekolah memperoleh skor tertinggi (5,0), sedangkan Pengadaan Buku & Media Ajar Agama Non-Muslim memiliki skor terendah (1,0). Sistem yang dibangun menggunakan PHP dan MySQL mampu menghasilkan perangkingan yang objektif dan terstruktur, sehingga dapat mendukung pengambilan keputusan yang lebih akurat dan konsisten
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".