The thesis topic similarity test with TF-IDF method

Authors

  • Sulartopo Sulartopo Universitas Sains dan Teknologi Komputer

DOI:

https://doi.org/10.51903/e-bisnis.v13i1.140

Keywords:

Term Frequency Inverse Document Frequency, Vector Space Model, extracting text, text similarity test.

Abstract

This research is to clarify how to test the thesis topic similarity, make it easy to check the topic thesis, whether it has been made by a student before. In this regard, an important issue that can be raised is how to make a thesis topic similarity test the manual way to be automated. The purpose of this study is a research method similarity of thesis topics using the TF-IDF method. In this research the system has two stages of process, the first mining the text that is categorizing the thesis that has been categorized using the TF-IDF algorithm, which is to read the appearance of each word in the contents of the document. The second stage results from the TF-IDF algorithm are reprocessed with the VSM algorithm. The end result of this program will get the names of documents that have a degree of similarity with keywords.

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Published

2020-07-01

How to Cite

Sulartopo, S. (2020). The thesis topic similarity test with TF-IDF method. E-Bisnis : Jurnal Ilmiah Ekonomi Dan Bisnis, 13(1), 13–16. https://doi.org/10.51903/e-bisnis.v13i1.140