<![CDATA[Infrastructure development, such as airports, often impacts the surrounding economic growth. On the one hand, the airport's economic growth is a desirable logical consequence. However, economic growth often occurs due to increased mining, industrial, plantation, trading, service, and other economic activities, causing changes in land use that do not follow the Spatial Planning and Regional Plans. Therefore, it may have implications for environmental damage. This paper proves a change in land use around Yogyakarta International Airport. Changes are observed through differences in land use in 2015, before the airport plan was built, and 2021, after the airport was operational. The random forest algorithm method is used to classify land use data sets. Furthermore, using the Multilayer Perceptron Neural Network Marcov Chain/ MLP NN-MC algorithm, it is predicted that the conversion of rice fields and plantations around the front side of the airport for housing and business will become even greater in 2030. Thus, the airport's construction has increased land use for business and residential purposes, while the green surface has been dramatically reduced. It was identified that there was a misuse of land use. Without good management, changes in land use can have an impact on decreasing environmental quality. Keywords: green infrastructure, land use change, land use prediction JEL Classification: Q57; R14; O44]]>
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