Intelligent simulator (i-Simulator) model for measuring the sustainability of Malaysian glutinous rice

The demand for glutinous rice in Malaysia has shown an increasing trend recently although supply from the local sector is critically low. In this regard, this innovation integrates artificial intelligence (AI) and system dynamics (SD) approaches, known as the Intelligent Simulator (i- Simulator) model to measure the sustainability of Malaysian glutinous rice by considering identified factors. In this research, the artificial intelligence method, specifically the artificial neural networks (ANN) model is developed to predict several crucial parameters. Subsequently, the best-sofar parameter from the ANN model will integrate cyclically with the stockflow diagram (SFD) based on the SD approach to investigate how a variable affects another variable. Then, the i-Simulator model is validated using a structured assessment. Finally, the model is evaluated through what-if analysis to capture the best impact on the glutinous rice industry. The expected outcome is a validated functional correlation among endogenous variables in a dynamic system. The significant outcome of this invention is the policy recommendation based on the evaluated correlation of endogenous variables which is in line with government policy to increase Self Sufficiency Level (SSL) to 90 percent in rice production.