Utilization of Market Organic Waste for Animal Feed as an Effort to Reduce Waste (Case Study: The Sumber Makmur Farmer Group, Gunung Tembak – Balikpapan)
Bibliographic record
Abstract
Managing the organic waste market in Balikpapan City is essential to reducing the burden on the Manggar Landfill. Organic waste, especially organic waste in the market, continues to increase along with the rapid growth of the population in Balikpapan City as a buffer city for Nusantara (New Capital City of Indonesia), which can increase the risk of environmental pollution and safety. Market organic waste can be used as an alternative feed for cattle and goats, and the Sumber Makmur Farmer Group, Gunung Tembak, Balikpapan City, has done this. Data collection for organic waste samples was conducted at Sepinggan Market, which has a sample size of 30 sample stalls. The organic market waste generation measurement technique refers to SNI 19-3964-1994 regarding Methods for Collecting and Measuring Waste Generation Samples with a data sampling time of 8 days (4 October 2024 – 11 October 2024). It was found that the average generation of market organic waste produced at Sepinggan Market was 452.67 kg/day. According to information from the Sumber Makmur Farmers Group, 26 cows and 26 goats are needed daily, and they need 500 kilograms of organic market waste as animal feed. These results prove there is still a difference or shortage of market organic waste of 47.33kg/day. This proves that using market organic waste such leftover vegetables or fruits can used for animal feed as an alternative to reducing market organic waste so that 100% is not immediately thrown into the Manggar Landfill, Balikpapan City. Keywords: market organic waste, farming, animal feed, Manggar Landfill
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".