Pengaruh perbedaan tegangan listrik pemanas terhadap performa mesin pendingin menggunakan refrigeran r-12, r134a, dan mc-134 di laboratorium prestasi Fakultas Teknologi Industri Universitas Trisakti
Bibliographic record
Abstract
Seiring dengan perkembangan teknologi dan pertambahan penduduk, kebutuhan akan air conditioner (AC) semakin meningkat, baik yang digunakan dalam industr i, perkantoran, gedung, perumahan, kendaraan, dan lainnya. Dalam penggunaan AC diperlukan refrigeran. Berdassrkan perjanjian montreal, disepakati penggant ia n refrigeran yang lebih ramah lingkungan. Refrigeran yang digunakan saat ini adalah refrigeran dengan senyawa CFC dan HCFC. Penggunaan refrigeran ini mengakibatka n ODP dan GWP. Penelitian ini bertujuan mengetahui efisiensi energi refrigeran R-12, R-134a, dan MC-134 dengan membandingkan nilai COP menggunakan mesin Refrigeration Laboratory Unit. Berdasarkan hasil pengujian, COP refrigeran MC-134 memiliki nilai paling tinggi dibanding refrigeran r12 dan R-134a, maka dapat disimpulkan bahwa refrigeran hidrokarbon MC-134 layak dipertimbangkan sebagai pengganti refrigeran R-12 dan R-134a, dengan tetap memperhatikan sifat mudah terbakar dari hidrokarbon pada temperatur tertentu.
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 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".