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Record W4214820943 · doi:10.29303/jpmpi.v5i1.1446

Pemberdayaan Masyarakat Desa Mujur Kecamatan Praya Timur Melalui Pemanfaatan dan Pelatihan dalam Mengolah Sampah Plastik Menjadi Kerajinan Tangan

2022· article· id· W4214820943 on OpenAlexaff
M. Hasan Murdani, Nadilla Yasmiadi, Yuliatin Yuliatin, Dadi Setiadi

Bibliographic record

VenueJurnal Pengabdian Magister Pendidikan IPA · 2022
Typearticle
Languageid
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsImmunoPrecise (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Sampah di Desa Mujur merupakan salah satu masalah yang belum terselesaikan hingga saat ini. Kurangnya kesadaran masyarakat tentang pengelolaan sampah mengakibatkan pencemaran dan kerusakan lingkungan, khususnya pada pengolahan limbah sampah plastik. Untuk itu pentingnya pengadaan penyuluhan pemanfaatan limbah sampah dan pelatihan pembuatan kerajinan tangan dengan menggunakan sampah plastik. KKN Terpadu Unram mengusung program pemanfaatan daur ulang sampah plastik agar dapat digunakan kembali atau diolah menjadi barang yang bermanfaat bagi lingkungan sekitar. Tujuan dari program ini adalah memberdayakan masyarakat Desa Mujur dalam pengolahan sampah menjadi kerajinan tangan menggunakan sampah plastik. Metode yang digunakan berupa pelatihan yang lebih berbasis pada praktik langsung, sosialisasi dan pembimbingan yang sifatnya monitoring. Hasil menunjukan bahwakegiatan tersebut dapat mengurangi limbah plastik dan juga dapat mengasah kreativitas masyarakat Desa Mujur saat mengisi waktu luang dirumah.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0300.008

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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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