Karyana, Dadang2022-10-272022-10-272022-07PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/10727Every year, student thesis research is increasing and with the addition of these documents, users will search for thesis titles with appropriate keywords. To make it easier for users to search for thesis titles, the author makes a system, namely a Vector Space Model-based thesis title search system which aims to make it easier for users to find thesis titles recommended by the system by knowing how accurate the search is. The vector space model method is used to measure the similarity between a document and a query. The basic concept of the method is to calculate the distance between documents and then sort them based on the level of proximity.The work principle starts with case folding, data cleaning, indexing, filtering, stemming, and tokenization, namely the cutting stage of the input string based on each word that compiles it and splitting the document into a word frequency table. All words in the document are formed into one, which is called a term. Each document is displayed as a vector which will be compared with the terms that have been formed. Lastly, Similarity Analysis to measure the similarity of documents is done by calculating the Cosine distance between the documents. The final results of the search for the title of the thesis using the vector space model method obtained the Cosine Similarity value where D3 has the highest value with a value of 0.09096, which means that D3 has the highest level of similarity with the query value. So that the documents that are expected to appear with a high degree of accuracy can be found precisely and the resulting documents are few.enCosine SimilarityDocumentThesis TitleQueryVector Space ModelArticle