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Record W4415208760 · doi:10.52232/jasintek.v7.i1.36

Pengelolaan Sampah Rumah Tangga Dan Pemanfatan Lahan Pekarangan Untuk Mendukung Pengembangan Desa Wisata

2025· article· id· W4415208760 on OpenAlexaff
I Ketut Arnawa, Putu Edi Yastika, I Gusti Bagus Udayana, I Made Budiasa

Bibliographic record

VenueJurnal Aplikasi dan Inovasi Iptek (JASINTEK) · 2025
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsAfforestationNational forestTerrace (agriculture)

Abstract

fetched live from OpenAlex

Sampah rumah tangga dapat mencemari lingkungan sehingga perlukan teknologi untuk mengolahnya. Kompos hasil pengolahan sampah rumah tangga dapat dimanfaatkan sebagai pupuk tanaman di lahan pekarangan. Tujuan utama penelitian ini adalah menggunakan teknologi tebe modern untuk mengolah sampah rumah tangga untuk pemupukan tanaman di lahan pekarangan. Penelitian dilaksanakan di Desa Petang Kabupaten Badung. Metode yang digunakan adalah penyuluhan, pelatihan dan aplikasi penggunaan hasil pengolahan sampah rumah tangga (kompos) untuk tanaman cabe, tomat dan terong di lahan pekarangan. Hasil penelitian menemukan hampir 89,38 % kelompok tani telah mengetahui dengan baik teknologi tebe modern pengolahan sampah rumah tangga menjadi kompos. Kelompok tani sudah berhasil membuat kompos dari sampah rumah tangga dan mengaplikasi pada tanaman cabe, tomat dan terong di lahan pekarangan. Penelitian ini menjadi sangat penting dilakukan untuk pengolahan sampah rumah tangga menjadi kompos dan diaplikasikan pada tanaman di lahan pekarangan untuk mendukung pengembangan desa wisata implementasi praktik budidaya berkelanjutan yang sejalan dengan prinsip green economy

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 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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.005
Science and technology studies0.0060.003
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.296
Teacher spread0.274 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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