HUBUNGAN SENSE OF BELONGING DENGAN PARTISIPASI MASYARAKAT PADA BANK SAMPAH DI WILAYAH KECAMATAN KEMAYORAN
Bibliographic record
Abstract
This objective of this study is to find the relationship of sense of belonging with community participation in waste banks in the Kemayoran District Area. This research was conducted with a quantitative approach. The population of this study was 134 residents who participated in the waste bank in the Kemayoran District Area. This research sampel is 100 residents who are administrator and customers the Waste Banks. Data analysis uses simple linear regression analysis test of correlation. The research releaved that there was a correlation beetwen sense of belonging and society participation in the waste banks seen from the calculation of the correlation between variables that is equal to r = 0,373 and the effective contribution of sense of belonging with society participation in the waste bank was 13,9% (r2 =0,139%). The results of these calculations indicate that the sense of belonging as a factor of participation is behind 13.9%. There other factors that influence the sense of belonging such as trust, the similarities that belong to organization members, age, social interaction and family functions which can motivate public participation in the garbage bank in the Kemayoran District Area by 86.1%. This research can be used as a reference for further research in the field of social and environmental sciences
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".