<![CDATA[Village infrastructure development plays an important role in improving community welfare. However, public opinion regarding the condition of infrastructure is often not analyzed comprehensively and based on data. This study aims to analyze public opinions toward infrastructure in Malitidari Village using the Unsupervised Learning method with the Orange application. The data were collected from public comments on social media and digital surveys, which were then processed in text format. The analysis process includes data preprocessing, tokenization, vectorization, and the application of a clustering algorithm to group opinions into several categories without prior labeling. The Orange application was used due to its ability to visualize data analysis workflows interactively and efficiently. The results of this study show that public opinions can be grouped into several main clusters: positive opinions related to the development of roads and public facilities, and negative opinions concerning delays and unequal quality of infrastructure. Based on these findings, the Unsupervised Learning method is proven effective in illustrating public perceptions of village infrastructure conditions. The results are expected to serve as a reference for the village government in planning and improving the quality of infrastructure development in Malitidari Village ]]>
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