<![CDATA[Document classification in the Financial and Asset Management Agency (BPKA) Kab. Deli Serdang is very important to do to facilitate the process of disposition of letters for all employees who are in the agency. However, currently the disposition of the letter at BPKA Kab. Deli Serdang has not been effective because it is still done manually. The process of disposition of letters that is done manually will take a long time and often mistakes are made by employees (human error) in determining the classification of documents because accuracy is needed in classifying documents. From the above problems, it can be concluded that the Financial and Asset Management Agency of Deli Serdang Regency is in dire need of a document classification system. In this case, there are several document classification methods, namely K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), Cosine Similarity, Naive Bayes and many other classification methods. And the Naive Bayes method is considered the most suitable in the application of document classification to the Financial and Asset Management Agency of Deli Serdang Regency. In this study, the author uses the Naive Bayes Algorithm method in classifying documents on the disposition of incoming letters at the District Financial and Asset Management Agency. Deli Serdang. With this research, it is hoped that it can help the Financial and Asset Management Agency of Deli Serdang Regency in conducting the disposition of letters]]>
