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Penggunaan Traktor Roda Dua pada Lahan Padi Sawah di Jawa Barat

2009· article· id· W2147352134 on OpenAlexaff
Saeful Bachrein, Agus Ruswandi, Trisna Subarna

Bibliographic record

VenueJurnal Agribisnis dan Agrowisata (Journal of Agribusiness and Agritourism) · 2009
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicAgricultural Research and Practices
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsForestryGeography

Abstract

fetched live from OpenAlex

Pengembangan komoditas padi sawah yang berorientasi agribisnis seharusnya didukung oleh alat dan mesin pertanian antara lain traktor moda dua. Kajian ini dilakukan untuk mengevaluasi tingkat penggunaan, keragaan dan kelayakan penggunaan traktor roda dua di lahan padi sawah di Jawa Barat. Kajian ini juga bertujuan untuk membuat pendekatan pengembangan traktor roda dua di Jawa Barat berdasarkan kenyataan di lapangan dan kebijakan pemerintah. Kajian ini dilaksanakan melalui metode Pemahaman Pedesaan Partisipatif dan survey terstruk-tur. Hasil pengkajian menunjukkan bahwa ketersediaan traktor relatif memadai dengan tingkat partisipasi rumah tangga pengguna di musim hujan dan kemarau masing-masing 96 % dan 97 %. Usaha jasa traktor layak diusahakan karena mem-berikan nilai Revenue-Cost Rasio 1,36 dan Pay Back Period 2,74 per tahun dan titik Impas 30,77 ha/tahun. Pada penelitian ini, beberapa masalah sosial, budaya dan teknis dalam pengembangan traktor roda dua pada padi sawah di Jawa Barat telah diinventarisasi.

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)0.003
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 score0.058
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0580.012

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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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

Citations5
Published2009
Admission routes1
Has abstractyes

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