Implementation of the Vector Space Model Algorithm for Document Searching in Material Test Monitoring Applications (Case Study: BPJN Jayapura Lab)
DOI:
https://doi.org/10.35799/jis.v24i1.52967Keywords:
Document search, Jayapura, vector space modelAbstract
The material test monitoring application built in 2021 aims to facilitate BPJN Jayapura's work in entering administrative data files to facilitate the material test monitoring process carried out from the process stage to the material test results stage. However, in using it for 2 years, the application has had problems. The application is unable to search for documents stored in the database so the search is carried out one by one. This makes it difficult for users because there are more than 30 documents. Therefore, this research will focus on creating a document search engine (search engine) using the Vector Space Model method. This algorithm will measure the level of similarity of documents to the keywords or queries entered by the user. This research implements the Vector Space Model method to make it easier to search for documents in the application. In carrying out this research, the Software Development Life Cycle methodology will be used as a method for creating the search engine using the Unified Modeling Language version 2.5.1 modeling tool and the PHP programming language. Based on the tests that have been carried out, the Vector Space Model method has been successfully implemented and is able to function as a search engine with a precision level of 0.83 and a recall of 1 for searching 40 documents as samples.
Keywords: Document search; Jayapura; vector space model
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
