<![CDATA[The diversity of development intensity and variation in regional characteristics, as well as various patterns of relationships between components, indicate the complexity of the study of the level of development sustainability in a region. To understand this complexity, a model is needed to provide an overview of the characteristics of regional development sustainability and the patterns of relationships that occur. The development of this model needs to be carried out through the development of an "intelligent system" to understand the structure of regional sustainability more precisely and comprehensively. The study aims to analyze the level of development sustainability of villages in Bantul Regency along with their spatial variations using Artificial Neural Networks (ANN) with the Kohonen-Self Organizing Maps Model topology. This study uses a quantitative and spatial approach through secondary data analysis from various sources. The secondary data to be processed is data from Bantul Regency up to the village level. To measure the level of development sustainability in Bantul Regency, we have identified 12 (twelve) variable themes that are crucial in understanding the complex nature of development sustainability. These themes include [list of themes]. The determination of the level of development sustainability is carried out through the use of Artificial Neural Networks (ANN) with the Kohonen-Self Organizing Maps Model topology. Data processing using Artificial Neural Networks (ANN) with the Kohonen-Self Organizing Maps Model topology is able to provide classification results that better reflect the characteristics of the cluster from the many variables used. Using self-organizing maps reduces complex data dimensions, making it easier to analyze. The findings of this study reveal that Bantul Regency mostly has a relatively low level of development sustainability. As many as 43 villages out of 75 villages in Bantul Regency have a low level of development sustainability or reach 58%. Only one percent have a high level of development sustainability, while the slightly high reaches 19%. These findings have significant implications for the development planning and resource allocation in Bantul Regency, highlighting the need for targeted interventions to improve development sustainability. This shows that in Bantul Regency, the level of development sustainability is still very varied.]]>
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