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Record W4390888196 · doi:10.32672/jse.v9i1.786

Optimalisasi Pelayanan TPS3R di Kelurahan Panjunan Menggunakan Metode Contingent Valuation Method

2023· article· en· W4390888196 on OpenAlex
Muhammad Farsya Indrawan Putra, Iwan Juwana

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Serambi Engineering · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsContingent valuationWillingness to payBiddingWork (physics)Delphi methodRegression analysisOperations managementBusinessStatisticsMathematicsEconomicsMarketingEngineering

Abstract

fetched live from OpenAlex

Recycling Facility Hikmah was built to provide solid waste management in the Panjunan Sub-district, Astanaanyar District, Bandung City. Recycling Facility Hikmah has the ability to operate continuously, but is still not running optimally due to cost constraints. This research was conducted to identify the potential for improving Recycling Facility management based on residents' willingness to participate in improving waste services through increasing retribution. The Contingent Valuation Method (CVM) is used as a survey technique using direct questionnaires and bidding game techniques, while statistical analysis will be carried out to determine the relationship between the observed variables. Based on the research results, the Willingness to Pay (WTP) value was obtained for 118 people from the 145 respondents interviewed. The Estimated WTP Value (EWTP) is IDR 6,822 and the Total WTP (TWTP) is IDR 4,848,866/month. Based on multiple linear regression analysis, the WTP value for Panjunan Village is influenced by the type of work and total income.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.255
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it