OPTIMASI ALGORITMA VECTOR SPACE MODEL DENGAN ALGORITMA K-NEAREST NEIGHBOUR PADA PENCARIAN JUDUL ARTIKEL JURNAL

  • Siti Fauziah Program Pascasarjana Magister Ilmu Komputer STMIK Nusa Mandiri
  • Daning Nur Sulistyowati Program Pascasarjana Magister Ilmu Komputer STMIK Nusa Mandiri
  • Taufik Asra Rekayasa Perangkat Lunak Universitas Bina Sarana Informatika
Keywords: Journal Title Search, Vector Space Model (VSM), K-Nearest Neghbour (KNN)

Abstract

Articles is one part of the scientific work which was manifested in the form of writing and containing a lot of information that are requisite and suited therein to the exclusion of .Many small article day with allah is as a variety of sorts of the title and the methodology that was used , but does not make up for the possibility of a resemblance of the title of the article that is there is .This study aims to for determining the rate of a resemblance between an article of the american journal of public from the point of view of the title of the articles the american journal of public by the use of an algorithm of vector space the model and compare it with an algorithm k-nearest neghbour .The data used pt pgn promised to supply 10 the title of an article of the american journal of public keyword on information retrieval .Testing the data with of these keywords documents produced by the only by the magnitude of the resemblance of its on the highest a method of vsm it will be on a doc 5 , doc 7 , doc 8 and doc 4 .While for the program knn generate a level of the resemblance of its on range doc7 , doc10| doc8 , doc10| doc4 , d10| doc5 , doc10| doc3 , doc10. So that came to the conclusion that the occurrence of the addition of the criteria used to they obtain documents they do similaritas keyword after

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Published
2019-03-07
How to Cite
Fauziah, S., Sulistyowati, D., & Asra, T. (2019). OPTIMASI ALGORITMA VECTOR SPACE MODEL DENGAN ALGORITMA K-NEAREST NEIGHBOUR PADA PENCARIAN JUDUL ARTIKEL JURNAL. Jurnal Pilar Nusa Mandiri, 15(1), 21-26. https://doi.org/10.33480/pilar.v15i1.27
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