Strengthening Rural Economies Through Integrated Agriculture: Evidence from Southeast Aceh Using Input–Output Modeling
Bibliographic record
Abstract
Rural economic areas in Southeast Aceh District face persistent development challenges, including low agricultural productivity, limited infrastructure, and economic disparities.This study proposes an Integrated Agricultural Model (IAM)-a synergistic approach that aligns crop production, livestock, and agro-industry-to foster rural transformation.Utilizing inputoutput modeling, forward-backward linkage analysis, and a Vector Error Correction Model (VECM), the study quantifies sectoral multipliers and dynamic interactions among agricultural output, the Farmer Exchange Rate (NTP), and rural GDP.The methodological framework combines secondary data (2015-2022) from the Central Bureau of Statistics (BPS) with field observations from 120 farmers across four districts.Results show that crop production exhibits the highest output multiplier (1.85), and agroindustry investments significantly enhance economic diversification.The VECM confirms that increases in agricultural output and NTP positively influence long-term rural GDP.Preliminary implementation of the IAM led to a 20% increase in farmer incomes, improved soil health, and higher community participation in agro-enterprises.These findings highlight the importance of integrated systems and intersectoral coordination as pathways to inclusive, sustainable development.The IAM provides a replicable model for rural transformation applicable across developing regions.
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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 | 0.001 | 0.002 |
| 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".