THE UTILIZATION OF GEO VISUALIZA THE UTILIZATION OF GEO VISUALIZATION TO DETERMINE THE FINAL WASTE DISPOSAL LOCATIONS IN BANYUMAS REGENCY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT
 
 The increasing population in Banyumas Regency has consequently impacted on the increasing amount of waste to manage. The old final waste disposal places are no longer capable to hold the amount of waste produced by the people of Banyumas Regency. Thus, Banyumas Regency has recently been in the emergency state dealing with its waste management. Banyumas Regency requires new final waste disposal locations since the old ones are no longer feasible. Thus, it is required to find new final waste disposal locations. This research employed a descriptive method with a spatial approach. The geographic information system (GIS) was performed to determine the final waste disposal locations by using the weighing and scoring method followed with the overlay maps. Those maps included the administrative map, river map, land-use map, waste-risk area map, flood-prone-area, landslide-prone area, earthquake-prone-area, fault map, slope map, rainfall map, and population density map. The results of this research show that the alternative final waste disposal locations in Banyumas Regency are best located in Kalibagor district covering the areas of Srowot, Kalisorga Wetan, Petir, and Pajerukan Village; while in Purwojati district covering the area of Purwojati and Karangtalun Kidul Village.
 
 Keywords: spatial analysis, Final Waste Disposal, waste
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it