Keywords
Archives Management
Classification
Naïve Bayes
Prototype
How to Cite
Abstract
Archival management is an important aspect of information management in various institutions, one of which is determining the retention status of archives. Determining the retention status of archives is still not accurate and effective, so there is a possibility of human error or inaccurate errors when determining the retention status of archives. One method that is appropriate for the problem is the classification method. The classification method used is Naive Bayes which will help archive operators. The purpose of this research is to classify the retention status of archives and create an application prototype. This approach allows archive managers to make more informed and efficient decisions about how to store or destroy documents, so they can reduce the risk of errors and optimize the use of storage space. The variables used are archive type, index type, active retention time, in-active retention time and class predictor, which is the archive retention status. Prototype application to determine archive retention status using the Naive Bayes Algorithm method. The test results using confusion matrix showed an accuracy of 96%, the accuracy of the user test questionnaire results was 100%, and the accuracy of the system expert test questionnaire results was 92.86%.
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