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Record W4406746250 · doi:10.20956/jdp.v10i1.41744

BIOKONVERSI LIMBAH PABRIK TEH DALAM MENINGKATKAN PENDAPATAN USAHA PRODUKSI PUPUK ORGANIK PADA PT. MADINA ANEKA SUBUR

2024· article· id· W4406746250 on OpenAlexaff
Harsani Haruna, Andi Besse Poleuleng, Dian Magfirah Hala, Andi Ayu Nurnawati, Susi Indriani, Rasbawati Rasbawati, Syarif Al Fajri, Mutmainna Mutmainna, Servianti Servianti, Yuki Yusbasari, Yulius Tina’ Para’pean

Bibliographic record

VenueJurnal Dinamika Pengabdian (JDP) · 2024
Typearticle
Languageid
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsWaste managementPulp and paper industryChemistryMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Proses pembuatan pupuk organik oleh PT Madina Aneka Subur memanfaatkan limbah pabrik teh berupa ampas sebagai bahan baku pupuk organik. Limbah ampas teh merupakan bahan organik dan memiliki berbagai macam kandungan. Masih awamnya pemahaman mengenai Maggot yang meliputi manfaat dan cara budidaya Maggot sehingga jarang yang memanfaatkan Maggot sebagai pengurai bahan organik. Pelatihan dan pendampingan ini bertujuan untuk meningkatkan pemahaman PT Madina Aneka Subur dalam mengelola limbah pabrik teh dalam meningkatkan pendapatan usaha produksi pupuk. Metode pelaksanaan pelatihan dilakukan dengan cara ceramah serta diskusi, sedanngkan pendampingan dilakukan dengan cara praktek di lokasi PT Madina Aneka Subur. Hasil kegiatan menjunukkan semangat dan antusias dari PT Madina Aneka Subur yang ingin memahami lebih lanjut proses pengolahan dengan memanfaatkan Maggot. Hal ini ditunjukkan pada saat kegiatan lanjutan berupa pendampingan budidaya Maggot. Kegiatan pelatihan dan pendampingan biokonversi limbah pabrik teh dengan memanfaatkan maggot berlangsung lancar dan sukses serta pemahaman peserta dari PT Madina Aneka Subur meningkat terkait pengolahan limbah pabrik teh dengan budidaya Maggot

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.007

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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
Published2024
Admission routes1
Has abstractyes

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