Assessing the Multidimensional Sustainability of Crystal Coconut Sugar Production in Banyumas Regency, Central Java, Indonesia
Bibliographic record
Abstract
Crystal coconut sugar is a product of indigenous knowledge which is very beneficial for health, as the population increases, the production of crystal coconut sugar needs to be increased and its sustainability maintained.Banyumas Regency is one of Central Java Province's main crystal coconut sugar-producing districts.The purpose of this study was to look at the sustainability of crystal coconut sugar by 1) assessing the multidimensional sustainability index as well as the state of crystal coconut sugar manufacturing; 2) evaluating the sustainability index in each of its dimensions (environmental, social, economic, and technological); 3) identifying the parameters that influence crystal coconut sugar systems; and 4) determining the most influential factors affecting crystal coconut sugar systems to enhance performance and production sustainably.This research used multidimensional scaling with four dimensions and 30 attributes.According to the findings of the analysis, the average performance shows a fairly sustainable status with a value of 65.42%.The economic dimension shows very good performance for sustainability, namely with a value of 90.86%, however, the environmental dimension features a value of 52.73%, and the technological dimension with a value of 49.83% shows less sustainability, while the social dimension with a value of 68.24% is fairly sustainable.For crystal coconut sugar production to have a good sustainable status, it is necessary to pay attention to leverage factors seen from low-value attributes to make improvements.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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 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".