Strategies for Optimising Rice Management in New Rice Expansion Areas in West Sumatra Province, Indonesia
Bibliographic record
Abstract
The West Sumatra provincial government from 2016 to 2018 implemented a new paddy field expansion programme.Currently, 73.33% of paddy fields are not managed by farmers.The paddy fields have been converted into plantations, buildings, and many are abandoned.The purpose of this study is to formulate strategies that can optimize the management of rice paddy farming in the location of new rice field expansion in the province of West Sumatra.This research uses mixed methods, combining quantitative methods with qualitative methods.The type of research used is survey research.The research location was determined by purposive technique, namely 8 districts where the implementation of new rice field expansion in West Sumatera Province.Respondents and research informants were selected using a purposive technique.The number of respondents was 48 paddy rice farmers and 22 informants from agricultural extension workers and Nagari government officials.The questionnaire data collection technique was used to obtain: a) data and information on the current condition of paddy rice farmland in the location of new rice field expansion; b) supporting and inhibiting factors in the management of paddy rice farming.In addition, interview techniques were used in conjunction with direct observation activities at the research site.Secondary data were obtained through documentation techniques, which were analyzed using the content analysis method.Qualitative data were analyzed using descriptive interpretative techniques, while quantitative data were analyzed using multivariate analysis techniques in Structural Equation Modeling -Partial Least Square (SEM-PLS).The results of this study are that only 26.67% of the new rice fields are managed by farmers.Strategies that can be used to optimize rice wetland management in new wet rice-expansion areas include optimizing agricultural extension to empower farmers' institutions and competencies, improving irrigation infrastructure, and utilizing wet rice farming technology.The strategy can be an input for the government in formulating policies to optimize the management of paddy farming in the location of new rice field expansion.The strategies formulated set this research apart from previous studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".