ABSTRACT:
Securing organizational data is an important information management issue that continues to pose significant challenges for organizations especially in Nigeria. Different organizations have made several failed attempts to develop authentic solution that will centrally create and manage document referential, place documents in their respective categories and apply retention on the documents during end-of-live, in a seamless manner. There have been several complaint from users on issues bordering on missing documents, premature destruction of important documents, organization's top-secret documents been found in wrong hands and placement of documents in wrong categories as a result of no well defined organizational policies . We developed an enhanced online document referential, classification and retention system, which combated these challenges. We used object oriented analysis and design methodology (OOADM) in our approach. Microsoft ASP.Net and Python technologies were used for this implementation. Automated document referential, classification and retention system provides a platform for easy creation of document referential, placement of documents in respective document categories and automatic application of retention on documents at the end of their lifespan. From the results, the overall accuracy of the classification model is 88% which indicates that most predictions made by the model are correct. The specificity of the individual classes ranges between ninety-eight (98) and one hundred (100) percent, whereas their precision, recall and f1-scores are above 0.5 which is good for prediction. This work could be beneficial to both small, medium and large-sized organizations.
Keywords:
Document, Referential, Retention, Classification
