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Record W3094045611 · doi:10.37277/stch.v25i1.144

Studi Persepsi Masyarakat Terhadap Pemanfaatan Energi Pada Rumah Tinggal

2018· article· id· W3094045611 on OpenAlexaff
Ima Rachima, Dian Maulina

Bibliographic record

VenueSainstech Jurnal Penelitian dan Pengkajian Sains dan Teknologi · 2018
Typearticle
Languageid
FieldComputer Science
TopicEnvironmental Engineering and Cultural Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesArt

Abstract

fetched live from OpenAlex

Abstrak---Penghematan energi merupakan topik bahasan yang mendapatkan perhatian serius terkait denganmakin mahalnya energi. Penghematan energi merupakan upaya mengefisienkan pemakaian energi untuk suatukebutuhan agar pemborosan energi dapat dihindarkan, khususnya pada bangunan gedung, tak terkecualibangunan rumah tinggal, khususnya dalam sistem pencahayaan dan penghawaan, karena mendiami rumahyang memiliki aliran udara yang sehat, memiliki penerangan alami yang cukup di siang hari merupakan faktorfaktoryang penting pada sebuah rumah tinggal. Penelitian ini sangat berperan dalam membantu pemahamanmasyarakat terhadap penggunaan energi listrik untuk penghawaan dan pencahayaan yang berdampak padapenghematan energi sehingga dapat memberikan edukasi kepada masyarakat agar lebih efisien dalampemakaian energi listrik. Target khusus pada penelitian ini adalah masyarakat di wilayah Kelurahan DepokJaya. Hasil penelitian menunjukkan sebagian besar koresponden memiliki pengetahuan dan persepsi yang baiktentang pemanfaatan energi pada rumah tinggal dan persepsi koresponden terhadap penghematan energiterbentuk dari perhatian mereka dalam upaya meringankan pembayaran penggunaan listrik mereka setiapbulannya, dari pengalaman mereka ini, akhirnya terbentuklah persepsi yang baik terhadap penghematanenergi.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.006

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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