System of Information Feedback on Archive Using Term Frequency-Inverse Document Frequency and Vector Space Model Methods

Dublin Core

Title

System of Information Feedback on Archive Using Term Frequency-Inverse Document Frequency and Vector Space Model Methods

Subject

Archive; Information retrieval; TF-IDF; Vector Space Model

Description

The archive is one of the examples of documents that important. Archives are stored systematically with a view to helping and simplifying the storage and retrieval of the archive. In the information retrieval (Information retrieval) the process of retrieving relevant documents and not retrieving documents that are not relevant. To retrieve the relevant documents, a method is needed. Using the Term Frequency-Inverse Document and Vector Space Model methods can find relevant documents according to the level of closeness or similarity, in addition to applying the Nazief-Adriani stemming algorithm can improve information retrieval performance by transforming words in a document or text to the basic word form. then the system indexes the document to simplify and speed up the search process. Relevance is determined by calculating the similarity values between existing documents by querying and represented in certain forms. The documents obtained, then the system sort by the level of relevance to the query.

Creator

Didit Suhartono a,*, Khodirun

Date

2020

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Citation

Didit Suhartono a,*, Khodirun, “System of Information Feedback on Archive Using Term Frequency-Inverse Document Frequency and Vector Space Model Methods,” Repository Horizon University Indonesia, accessed June 6, 2025, https://repository.horizon.ac.id/items/show/9213.