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Record W2341697101 · doi:10.29244/jitl.16.1.24-30

POTENSI LAHAN UNTUK KOLAM IKAN DI KABUPATEN CIANJUR BERDASARKAN ANALISIS KESESUAIAN LAHAN MULTI KRITERIA

2014· article· id· W2341697101 on OpenAlexaff
Wuri Cahyaningrum, Widiatmaka Widiatmaka, Kadarwan Soewardi

Bibliographic record

VenueJurnal Ilmu Tanah dan Lingkungan · 2014
Typearticle
Languageid
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Kabupaten Cianjur merupakan salah satu wilayah yang potensial untuk pengembangan budidaya ikan air tawar. Sampai saat ini, proporsi terbesar dari total produksi ikan berasal dari Keramba Jaring Apung (KJA) Waduk Cirata. Waduk Cirata saat ini sudah dan sedang mengalami penurunan kualitas sehingga mengurangi produksi ikan Kabupaten Cianjur. Oleh karena itu, diperlukan alternatif cara pemeliharaan ikan selain KJA. Salah satunya adalah kolam. Informasi mengenai wilayah yang berpotensi untuk lokasi budidaya ikan merupakan faktor penting dalam pengembangan perikanan. Penelitian ini bertujuan untuk memetakan tingkat kesesuaian lahan untuk kolam. Penentuan kesesuaian lahan dilakukan dengan aplikasi Sistem Informasi Geografis (SIG) dan Evaluasi Multi-kriteria (Multi Criteria Evaluation, MCE). Hasil analisis kesesuaian lahan menunjukkan lokasi yang sesuai untuk kolam seluas 86,511 ha (23.9% dari total luas wilayah). Hasil analisis terhadap lahan yang sesuai, lokasi yang tersedia seluas 74,062 ha (20.5%) dan yang tidak tersedia seluas 12,449 ha (3.44%). Hasil penelitian menunjukkan bahwa pengembangan lahan untuk kolam masih mungkin dilakukan di Kabupaten Cianju

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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 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

Citations7
Published2014
Admission routes1
Has abstractyes

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