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ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PRODUKSI KOPI ROBUSTA DI KABUPATEN BANYUWANGI

2022· article· id· W4306864054 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Javanica · 2022
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Management
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMathematicsPhysicsHorticultureForestryBiologyGeography

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi produksi kopi robusta di Kecamatan Kalipuro Kabupaten Banyuwangi. Penentuan lokasi penelitian ini dilakukan secara sengaja (purposive) dengan pertimbangan daerah yang dipilih merupakan sentra produksi kopi. Data penelitian ini diperoleh dari kuesioner (primer) dan observasi serta wawancara langsung dengan pihak yang terkait dengan produksi kopi di Kecamatan Kalipuro Kabupaten Banyuwangi. Hasil penelitian ini menunjukkan bahwa nilai adjusted R square sebesar 0,928 yang berarti bahwa sekitar 92,8% produksi kopi robusta secara bersama-sama dipengaruhi oleh variabel (luas lahan, tenaga kerja, pupuk anorganik, dan bibit) dan sisanya 7,2% diterangkan oleh variabel lain yang tidak terdapat dalam penelitian ini. Secara persial variabel luas lahan (X1) berpengaruh signifikan, variabel tenaga kerja (X2) tidak berpengaruh signifikan, variabel pupuk anorganik (X3) berpengaruh signifikan, dan variabel bibit (X4) berpengaruh signifikan terhadap produksi kopi di Kacamatan Kalipuro Kabupaten Banyuwangi.

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.

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.019
GPT teacher head0.202
Teacher spread0.183 · 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