HUBUNGAN KARAKTER PERMUKIMAN DENGAN PARTISIPASI MASYARAKAT DALAM PENGELOLAAN SAMPAH RUMAH TANGGA (STUDI KASUS : SURODADI, KELURAHAN SISWODIPURAN DAN PERUM BUMI SINGKIL PERMAI I DESA KARANGGENENG, KECAMATAN BOYOLALI)
Bibliographic record
Abstract
Every citizen who lived in settlements will definitely produce garbage, therefore the volume of waste continues to increase every time. While the final disposal is provided having a limited capacity, so that we waste management at the community level needs to be improved so that the amount of waste that goes to landfill can be reduced. Waste management at the community level is also done in Surodadi, Siswodipuran and Perum Bumi Singkil Permai (BSP) I, Karanggeneng, Boyolali. But to these two regions have different treatment in processing waste. The problem in this research is about how are the relations between the residential character and the community participation in waste management. The methos used is the methos of description that describes the relationship between the two factors through the depiction of the results of observations, questionnaires and interviews. The results of this study are the difference in terms of residential character, wate management system and participation from the community in garbage penelolaan in both regions. Economic conditions have relation with the community participation in the management of household waste. Livelihood, social, and cultural interactions taht evolve shown to has a relation with the community participation in the management of household waste. The level of income and education levels have no connection with participation from the community in waste management. Keyword : Community Participation, Residentials, Waste Management
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".