Abstract
Chicken meat agroindustry is one of the industries that produce unmeasured and unmonitored environmental impacts. These problems are a challenge for the industry to analyze how to measure and monitor environmental impacts. So, it is necessary to create a system that can measure and monitor environmental impacts through the Life Cycle Assessment (LCA) method. The development of system design based on the Digital Business Ecosystem (DBE) can facilitate interaction between the stakeholders involved. This study aimed to analyse system components, system modeling, and develop an LCA system design of chicken meat. The system design model wasbuilt by UML (Unified Modeling Language). The system design was developed using an Artificial Neural Network (ANN) method to predict the impact of greenhouse gas emissions and the Ordinary Least Squares (OLS) method to determine the most significant contributor. The study's results showed that this system produceed a model that can predict the impact of greenhouse gas emissions by 96.22 % of the actual value, and feed was the most significant contributor. Recommendations for reducing greenhouse gas emissions were increasing feed efficiency, installing an inverter on an ammonia compressor, using environmentally friendly fuels, and utilizing litter and manure as organic fertilizer accompanied by better manure storage management.Keywords: artificial neural network, chicken meat, ordinary least square, life cycle assessment system
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