<![CDATA[This research explores the application of Cosine Similarity and TF-IDF (Term Frequency-Inverse Document Frequency) techniques for analyzing community complaints in Pertumbukan Village, Wampu District, through a web-based system. The increasing volume of community complaints requires an efficient method to categorize and analyze the ual data, enabling village authorities to prioritize and address the issues more effectively. By implementing Cosine Similarity, the system measures the similarity between complaint documents, helping to identify recurring themes or issues. TF-IDF is used to weigh the importance of terms in the complaint dataset, allowing the system to highlight significant concerns based on the frequency of keywords in each document. The integration of these techniques in a web-based platform offers an accessible and scalable solution for complaint management. The system is tested using real complaint data from the community, and the results show that this approach improves the accuracy and efficiency of complaint categorization. This research contributes to the development of more responsive public service systems in rural areas.]]>
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