Implementasi Metode Analytical Hierarchy Process Dan Interpolasi Linier Dalam Penentuan Lokasi Wisata Di Kabupaten Karangasem
Why this work is in the frame
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Bibliographic record
Abstract
Bali is known for its tourism sector, so it has always been one of the alternative tourist destinations for local and foreign tourists. Almost every district in Bali has interesting tourist attractions to visit for tourists. When traveling, tourists usually decide to visit interesting tourist destinations. The number of tourist destinations available, often makes tourists confused about choosing a destination according to their preferences. Therefore, this research is intended for tourists to be able to determine alternative priority tourist sites in Karangasem Regency. In this study, data were collected from 75 respondents to find out alternative tourist sites in Karangasem, and to determine the criteria to be considered for traveling. These criteria are rides provided at tourist sites (C1), price of admission to tourist sites (C2), distance from tourist sites to city center (C3) and facilities provided at tourist sites (C4). 4 alternative tourism data used in the calculation by producing alternative tourist sites at Taman Ujung as the best alternative. The method used is the Analytical Hierarchy Process (AHP) to produce the weighted criteria, scoring the ticket price and distance values using Linear Interpolation and calculating the final value using the Cost and Benefit normalization process. The results of this study can provide alternative tourist locations for domestic tourists who want to vacation in Karangasem Regency.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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 it