<![CDATA[This research develops an artificial intelligence-based letter archiving management information system for the GPI Papua Classis Mimika Institute in Central Papua, with a focus on classifying incoming letters using the Naive Bayes algorithm. The aim of this research is to make it easier to search and monitor documents and increase the efficiency and accuracy of mail archive management. The dataset consists of 50 data, of which 20 data are spam mail data and 30 non-spam mail data. Test results using the Confusion Matrix method show that the system has an accuracy of 78%, precision of 88% for the spam category, recall of 73.3% for the spam category, and an F1 Score of 79.9%. It is hoped that the application of AI technology can help the GPI Papua Klasis Mimika Institute in Central Papua in optimizing the incoming letter classification process, minimizing errors and increasing the efficiency of document management. By using an AI-based approach, the system can also provide practical solutions for more effective and efficient archive management, thereby enabling access to the required information quickly and precisely. Overall, the application of AI technology in mail archiving is expected to not only increase productivity and accuracy, but also provide a strong foundation for improving service and operational efficiency in various sectors and institutions.]]>
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