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Record W2977034096 · doi:10.24843/bum.2019.v18.i01.p16

VERMIKOMPOS SAMPAH TANAMAN GULMA DANAU MENGGUNAKAN DECOMPOSER CACING TANAH UNTUK MENGHASILKAN PUPUK ORGANIK

2019· article· id· W2977034096 on OpenAlexaff
I.G. Suranjaya, Ni Luh Kartini, N.L.R. Purnawan, P.E. Suardana

Bibliographic record

VenueBuletin Udayana Mengabdi · 2019
Typearticle
Languageid
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsForestryHumanitiesArtGeography

Abstract

fetched live from OpenAlex

Kegiatan pemberdayaan masyarakat ini merupakan bagian Program Kemitraan Wilayah (PKW) yang bertujuan untuk alih teknologi dalam produksi vermikompos berbasis sampah dari tumbuhan gulma danau dengan menggunakan decomposer cacing tanah (Lumbricus rubelus) untuk menunjang pengembangan pertanian ramah lingkungan di seputaran danau Buyan desa Pancasari, Kecamatan Sukasada, Kabupaten Buleleng. Metode yang diterapkan dalam pemberdayaan masyarakat pada kegiatan program PKW adalah sebagai berikut: (1) Koordinasi dan sosialisasi secara partisipasif kepada masyarakat sasaran untuk merumuskan kegiatan yang akan dilaksanakan mulai dari perencanaan, operasional dan evaluasi; (2) Penyuluhan untuk membangun persepsi dan pemahaman masyarakat mengenai inovasi atau program yang ditawarkan; (3) Pelatihan dan simulasi mengenai terapan ipeks yang dialihkan bagi masyarakat; (4) Pendampingan yaitu pertemuan secara berkala antara pendamping dengan masyarakat sasaran hingga ipteks yang dialihkan dapat dilaksanakan secara mandiri oleh masyarakat. Hasil yang diperoleh menunjukkan bahwa kegiatan pemberdayaan masyarakat dalam produksi vermikompos berbasis sampah tumbuhan gulma danau sebagai upaya menunjang pengembangan pertanian ramah lingkungan dapat berlangsung dengan baik dan lancar yang ditunjukkan dengan adanya partisipasi aktif dan daya adopsi ipteks yang tinggi dari masyarakat sasaran. Partisipasi aktif masyarakat sasaran dalam seluruh kegiatan alih teknologi ini cukup baik, yaitu sebesar 75%. Kemampuan adopsi ipteks dan inisiatif mitra untuk memproduksi vermikompos secara mandiri juga cukup baik, yaitu rata-rata diatas 65%.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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 designBench or experimental
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

Citations1
Published2019
Admission routes1
Has abstractyes

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