MOBILE APPLICATION GREEN INDUSTRY BERBASIS CLOUD UNTUK MANAGEMENT DATA WAREHOUSE PADA UKM MENGGUNAKAN TEKNOLOGI QR CODE
Bibliographic record
Abstract
Penelitian ini bertujuan untuk membuat suatu aplikasi sistem manajemen data pada UKM atau perusahaan dengan memanfaatkan penyimpanan berbasis Cloud serta teknologi penerjemah QR Code dalam satu software untuk memudahkan dalam sisi fleksibilitas. Metode yang digunakan dalam pembangunan sistem ini menggunakan System Development Life Cycle (SDLC) dengan pendekatan model waterfall. Hasil penelitian ini menunjukkan bahwa sistem ramah lingkungan diterapkan untuk mendorong UKM atau perusahaan dalam mengurangi tingkat penggunaan energi sekaligus biaya hingga 60% pada proses pengaplikasiannya. Kata kunci: ramah lingkungan, Cloud, QR Code, manajemen data.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".