Optimizing rice production inputs for enhanced smallholder income: An agent-based modeling and simulation approach - Muhammad Rusman; Annisa Almukarramah; Dwi Handayani (Journal Industrial Servicess, 2026)
Rice production output among farmers in rural areas varies across individuals, leading to income disparities. These differences are influenced by variations in farmers’ behavior in managing rice cultivation, which directly affect production levels. To capture this dynamic, this study develops an agent-based modelling and simulation (ABMS) approach to represent the rice production process. The objective is to design a model that describes the roles, behaviors, and interactions of agents and to formulate improvement scenarios for system performance. Data were collected through interviews with farmers and middlemen. The simulation was implemented using NetLogo 6.3.0, following stages of conceptual model development, problem formulation, model construction, verification and validation, and scenario development. The model consists of three agents: farmers, rice plants, and pests. Farmers act as decisionmakers by controlling production inputs that influence plant–pest interactions. The simulation was executed 130 times using different input combinations, including a fixed seed quantity of 40 kg, fertilizer ranging from 100–1000 kg (100 kg intervals), and pesticide ranging from 400–1000 g (50 g intervals). The results show that the optimal scenario—40 kg seeds, 400 kg fertilizer, and 400 g pesticide—can increase farmers’ income by IDR 2,742,472 compared to actual conditions. Overall, the ABMS approach effectively captures interactions among agents and provides a scenario that improves rice production performance and farmer income.