Irrigation systems play a crucial role in enhancing rice production. However, determining the optimal method for irrigation system optimization using conventional approaches is often challenging. This study aims to identify the optimal irrigation system represented by the water table level using a Genetic Algorithm (GA) model. The GA model was chosen for its advantages in addressing non-linear problems and finding global solutions without being trapped in local optima. The model was developed based on a laboratory-scale rice cultivation experiment involving four water table treatments: 0–7 cm with oxygen enrichment via Fine Bubble Technology (TA1), 4–7 cm (TA2), –5 to 0 cm (TA3), and 2–4 cm (TA4) above the soil surface. The research was conducted from February to June 2024 at Kinjiro Farm, Bogor City. The four treatments produced varying yields, with TA 2 achieving the highest yield of 6.86 tons/ha, followed by TA1 (5.35 tons/ha), TA3 (5.00 tons/ha), and TA4 (4.80 tons/ha). Based on these data, the GA model successfully identified the optimal water table level of 3.5 cm above the soil surface, which could increase production to 7.40 tons/ha. This water level represents a moderate irrigation depth, requiring a medium level of irrigation compared to the four tested treatments perlakuan.
                        
                        
                        
                        
                            
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