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Record W4413332797 · doi:10.29313/bcsurp.v5i2.20163

Faktor – Faktor yang Mempengaruhi Pelaksanaan Usahatani Padi di Kecamatan Karangtengah, Kabupaten Cianjur

2025· article· en· W4413332797 on OpenAlexaff
S.Kep.Ns. Ira Rahmawati, Saraswati

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Abstract. Karangtengah Subdistrict, located in Cianjur Regency, is one of the strategic areas for food production in West Java Province. However, this region faces various complex challenges in the implementation of rice farming, including the conversion of 209 hectares of paddy fields during the 2006–2019 period, significant population growth, and limited access to markets and agricultural infrastructure. These issues have direct implications for the effectiveness and sustainability of rice farming systems, thereby necessitating a comprehensive analysis to identify the key factors influencing its implementation. This study aims to analyze the availability and demand for rice in Karangtengah Subdistrict and to identify the factors that influence the implementation of rice farming. A quantitative approach was employed, utilizing methods such as rice surplus and deficit analysis, as well as multiple linear regression analysis. Data collection was conducted through the distribution of questionnaires to 323 farmers and interviews with relevant institutions. The findings indicate that, despite annual fluctuations in availability, Karangtengah Subdistrict generally experiences a rice surplus. Based on the results of the multiple linear regression analysis, five variables—accessibility, farming experience, availability of capital, rainfall, and pest and disease outbreaks—were found to significantly affect the implementation of rice farming. Collectively, these five variables account for 70% of the variation in the implementation of rice farming in the study area. Abstrak. Kecamatan Karangtengah, Kabupaten Cianjur merupakan salah satu wilayah strategis dalam penyediaan pangan di Provinsi Jawa Barat. Namun demikian kawasan ini menghadapi berbagai tantangan yang kompleks dalam pelaksanaan usahatani padi antara lain alih fungsi lahan persawahan seluas 209 hektar selama periode 2006–2019, pertumbuhan jumlah penduduk yang signifikan, serta keterbatasan akses pasar dan infrastruktur pertanian. Permasalahan-permasalahan tersebut berimplikasi langsung terhadap efektivitas dan keberlanjutan sistem usahatani padi sehingga diperlukan analisis yang komprehensif untuk mengidentifikasi faktor-faktor yang menentukan pengaruh terhadap pelaksanaannya. Penelitian ini bertujuan untuk menganalisis ketersediaan dan permintaan padi di Kecamatan Karangtengah, serta mengidentifikasi faktor-faktor yang mempengaruhi pelaksanaan usahatani padi. Penelitian menggunakan pendekatan kuantitatif dengan metode analisis yang terdiri atas analisis surplus dan defisit beras, dan analisis regresi linear berganda. Pengumpulan data dilakukan melalui penyebaran kuesioner kepada petani sebanyak 323 petani serta wawancara dengan instansi terkait. Hasil penelitian menunjukkan bahwa meskipun terdapat fluktuasi ketersediaan antar tahun Kecamatan Karangtengah secara umum mengalami surplus beras. Berdasarkan hasil analisis regresi linear berganda, ditemukan bahwa lima variabel yaitu aksesibilitas, pengalaman bertani, ketersediaan modal, curah hujan, serta serangan penyakit dan hama berpengaruh secara signifikan terhadap pelaksanaan usahatani padi. Kelima variabel tersebut secara simultan memberikan kontribusi sebesar 70% terhadap variasi pelaksanaan usahatani padi.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.296
Teacher spread0.254 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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