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Sustainable Environmental Management System in Food Crop Agriculture in Wonosobo District, Indonesia


 The sustainability level needs to be measured and analyzed comprehensively using a representative measurement model. The main objective of this study was to develop a sustainable environmental management system for food crop agriculture. The proposed hybrid measurement model integrates the inventory of greenhouse gas (GHG) effects and geographic information systems (GIS) with the Internet of Things (IoT). The proposed model was implemented in a potato farming system in six sub-districts in Wonosobo, Indonesia. From an environmental perspective, that is, methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O), emissions were measured using the Raspberry Pi. Then, we added GHG spatial mapping by considering the environmental quality index. Sustainability levels were classified into three classes. We then measured the economic viability, social acceptance, and spatial perspective index (Si). The results showed that the value of sustainability was >0.1 without considering Si, meaning that all samples showed conditions above the threshold for sustainability. However, after adding Si, namely altitude, slope, soil texture, temperature, and rainfall, the N1 and N2 samples had values >0.1. In contrast, N4 and N6 showed values <0.1. The proposed model can measure and analyze the sustainability of a sustainable food crop system. This model has also successfully proposed a strategy by increasing environmental sustainability in the Garung sub-district using the ANP Super Decision. We propose an alternative strategy: government regulation, strengthening agricultural institutions, disseminating emissions and environmental aspects, and academic assistance. In future research, this model can be used to control CH4, CO2, and N2O emissions.