Rancang Bangun Web Service Sistem Informasi Keuangan GMIM Wilayah Tomohon 3
Bibliographic record
Abstract
Bertambahnya warga Gereja secara terus-menerus menyebabkan pertambahan data yang cukupsignifikan pada Gereja-Gereja, baik itu data jemaat, datakeuangan dan data-data lainnya. Arus informasi keuanganGereja sangat dibutuhkan untuk mengetahuiperkembangan Gereja dari sisi finansial, bagaimanastruktur modal, berapa pemasukan dan pengeluaran padasatu periode tertentu. Pengelolaan data keuangan diGMIM Wilayah Tomohon 3 masih dilakukan dengan caramanual yang kurang efektif dan efiesien sehinggamenyebabkan tidak maksimalnya proses pengelolaan datayang ada. Oleh karena itu dibuatlah sebuah aplikasi WebService Sistem Informasi Keuangan GMIM Wilayah 3untuk mengatasi permasalahan pengelolaan data keuanganyang ada.Metode pembuatan aplikasi ini menggunakan metodeperancangan sistem Rapid Application Development (RAD),yang dimulai dengan tahap analisis persyaratan yangdilakukan dengan membuat problem statement matrix.Tahap selanjutnya, design workshop (pemodelan)digambarkan dengan proses bisnis, structural model danbehavioral model, serta human computer interaction layerdesign. Tahap terakhir, implementasi (konstruksi)dijelaskan dengan implementasi basis data dan kodesumber program.Kata Kunci : Gereja, Rapid Application Development(RAD), Sistem Informasi Keuangan, Web Service
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.020 |
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".