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
Collection
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/9210.