STUDI KESESUAIAN PENERAPAN STANDAR LINGKUNGAN PERUMAHAN SEDERHANA SEHAT DI KOTA SERANG
Bibliographic record
Abstract
Serang city is the Capital City of Banten Province. As the time goes by, the population increases and the poor people needs an access to have a home. There are two housing environments, which is called “simple healthy housing environment” to help the poor people ,which are Banten Indah Permai and Bumi Serang Timur, but the condition is the housing environments are lack of infrastructures and facilities. This problem makes a question how the suitability of simple healthy housing environment in Kota Serang is. The suitability study of simple healthy housing environment in Serang city is done by using scoring method analysis to count the suitability of the simple healthy housing environment standards as the output and perception of the people inside the housing environment as the outcome of this simple healthy housing environment. Descriptive comparative analysis is used also to know how output and outcome can match each other in the housing environment. Final scoring result obtained that Banten Indah Permai has been classified as suit in output because of the 58 score , but Bumi Serang Timur is not suit in output because it has 55 score. In outcome scoring, Banten Indah has been classified as suit in outcome for the 76,94 score, and also for Bumi Serang Timur has 75,68 for the outcome score. With comparative analyisis, this study also obtained that there are many infrastructure and facilities in housing environment which are not give the outcome as usual the housing environment gives. Keywords: simple healthy housing, suitability, scoring, environment,
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".