Open AccessThe thesis topic similarity test with TF-IDF method
Author(s) -
Sulartopo Sulartopo
Publication year - 2020
Publication title -
e-bisnis
Language(s) - English
Resource type - Journals
eISSN - 2614-8870
pISSN - 1979-0155
DOI - 10.51903/e-bisnis.v13i1.140
Subject(s) - tf–idf , similarity (geometry) , computer science , information retrieval , test (biology) , word (group theory) , natural language processing , data mining , artificial intelligence , mathematics , paleontology , physics , geometry , quantum mechanics , term (time) , image (mathematics) , biology
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.