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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control)
Naila Maulidina Lu'ayya
Universitas Brawijaya
Computer Science & IT Engineering

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Artificial intelligence-based risk assessment in agro-industry using supervised neural networks Imam Santoso; Izzum Wafi'uddin; Naila Maulidina Lu'ayya; Annisa'u Choirun; Siti Asmaul Mustaniroh; Dodyk Pranowo; Ainur Rofiq
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2260-2268

Abstract

The coffee supply chain involves high production volumes, complex multi actor interactions, and increasing sustainability requirements, yet remains highly vulnerable to risks dimension. This study aims to develop and evaluate a decision-support framework that improves the accuracy and consistency of sustainability risk classification in the coffee supply chain. The proposed framework integrates failure mode and effect analysis (FMEA) with a supervised artificial neural network (ANN) using backpropagation (BP) to enable data-driven and adaptive risk assessment. Empirical data was collected from 55 respondents, resulting in the identification of 35 supply chain risk factors. These data were used to train and validate an ANN-based classification model implemented in a Python environment, with standard preprocessing and stratified data partitioning to ensure robustness. The ANN classified risks into five categories using supervised learning. The results demonstrate strong predictive performance, achieving overall accuracy of 98.97%, with precision, recall, and F1-scores exceeding 96.8% across all risk classes. Confusion matrix analysis confirms reliable generalization and minimal misclassification. The findings indicate that integrating FMEA with ANN-BP significantly enhances risk classification compared to conventional qualitative approaches. The proposed framework provides a scalable and reliable decision-support tool for dynamic risk scoring, supporting enhancement of sustainable practices in agro-industrial coffee supply chains.
System dynamics control simulation for sustainability of Indonesia’s cocoa supply chain Imam Santoso; Dodyk Pranowo; Hendrix Yulis Setyawan; Izzum Wafi'uddin; Naila Maulidina Lu'ayya; Annisa'u Choirun
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27509

Abstract

Indonesia’s cocoa sector faces challenges in greenhouse gas emissions and smallholder income volatility. This study develops a system dynamics model to simulate the interrelationship between carbon emissions and economic performance across the cocoa value chain, identify leverage points, and evaluate alternative policy scenarios. The model integrates environmental and economic variables into dynamic feedback structures, enabling scenario-based assessment of intervention strategies. Five scenarios were simulated: composting cocoa waste increased farmer income by 2% and reduced farm-level emissions from 0.43 to 0.303 kg CO₂-eq/kg (29.79% total reduction); biogas conversion raised income by 13.56% and reduced emissions by 11%; converting cocoa waste into animal feed slightly increased income by 0.23% while cutting emissions by 58.6%; combining composting with improved transport efficiency reduced emissions by 14%; and integrating composting, logistics optimization, and government-supported input subsidies yielded the highest performance, with a 13.50% income increase and a 70% emission reduction. These results demonstrate that integrated, system-based interventions can enhance both economic resilience and environmental sustainability. The system dynamics model provides policymakers and supply chain actors with actionable insights for designing effective, climate-aligned strategies in Indonesia’s cocoa industry.
Co-Authors Ainur Rofiq Annisa'u Choirun Annisa'u Choirun Dodyk Pranowo Dodyk Pranowo Imam Santoso Izzum Wafi'uddin Setyawan, Hendrix Yulis Siti Asmaul Mustaniroh