Perencanaan home industry pudding “Nutri Pudding” dengan kapasitas 100 Cup (@155 g) per hari
Bibliographic record
Abstract
Pudding merupakan salah satu jenis makanan penutup (dessert) \nyang digemari dan dikonsumsi oleh banyak orang. Pudding juga sering dijadikan cemilan pada waktu senggang terutama wanita karena mudah diperoleh dan dikonsumsi. Perencanaan unit pengolahan pangan pudding “Nutri Pudding” memiliki kapasitas 100 cup (@155 g) per hari. Lokasi unit pengolahan direncanakan di Jalan Telasih No. 12, Ketabang, Surabaya.Bentuk badan usaha berupa Industri Rumah Tangga Pangan dengan jenis usaha mikro. Struktur organisasi lini terdiri dari 1 manager dan 1 karyawan. Bahan baku yang digunakan yaitu Nutrijell pudding susu rasa cokelat, susu UHT full cream, agar-agar, air minum, gula pasir, dan biskuit “Marie”. Proses pengolahan terdiri dari pencampuran, pemanasan, pengisian dalam cup, dan pendinginan. Kemasan yang digunakan berupa cup plastik Polyethylene terephthalate (PET) bertutup dengan volume 150 mL. Utilitas yang \ndigunakan meliputi air 108.720 L/tahun, listrik 689,28 kWh/tahun, gas LPG 48 kg/tahun, dan Baterai AA 24 pcs/tahun. Penjualan akan dilakukan dengan sistem PO (Pre-Order) akan dibuat sesuai permintaan konsumen. Pendirian usaha ini memiliki laju pengembalian modal (ROR) sebelum pajak 28,05% \ndan ROR setelah pajak 29,40% yang lebih besar dari nilai MARR (Minimal Attractive Rate of Return) 13,25%. Waktu pengembalian modal (POT) sebelum pajak 3 tahun 4 bulan dan POT setelah pajak adalah 3 tahun 5 bulan. Titik impas (BEP) sebesar 71,69%. Berdasarkan faktor teknis dan ekonomi, \nunit pengolahan pudding “Nutri Pudding”’ layak didirikan.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.072 | 0.024 |
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".