SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PENERIMA KIP-KULIAH MENGGUNAKAN METODE SMART
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Indonesia memiliki program beasiswa KIP-Kuliah guna mewujudkan UUD 1945 pasal 28C ayat 1, yang mana Indonesia menjamin hak masyarakat untuk mendapatkan pendidikan yang layak. Adapun pada penelitian ini, penulis mencoba untuk membuat sebuah sistem pendukung keputusan yang harapannya dapat membantu dalam pengambilan keputusan penerima KIP-Kuliah khususnya di Universitas Malikussaleh. Pada penelitian ini, digunakan metode SMART sebagai metode perhitungan untuk memprioritaskan penerima KIP-Kuliah dengan lebih efisien dan tepat sasaran. Hasil yang diperoleh dari pengurutan menggunakan metode SMART yaitu terdapat perolehan ranking penerima KIP-Kuliah dari paling prioritas hingga tidak prioritas berdasarkan atribut-atribut yang telah ditetapkan. Perankingan ini nantinya dapat dijadikan sebagai acuan untuk proses seleksi penerima beasiswa KIP-Kuliah.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.005 |
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 it