A IMPLEMENTASI TERM FREQUENCY â€“ INVERSE DOCUMENT FREQUENCY (TF-IDF) DAN VECTOR SPACE MODEL (VSM) UNTUK PENCARIAN BERITA BAHASA INDONESIA - Wiyanto W; Wowon Priatna; Jumi Saroh Hidayat (Jurnal Pelita Teknologi, 2019)
A search engine that already exists and widely used today can be provide the result of information very much, so it takes time to sort through the information in need. The research with the title "The â€œimplementation term frequency-inverse document frequency (TF-IDF) and vector space model (VSM) to search a news of Indonesian languageâ€ have a purpose to develop the method of quick search uses TF-IDF method and vector space model. There are two main processes in the search system of news that are indexing and retrieval. The process of indexing is a process to give assessment to the words on document, the method of assessment in this research uses an assessment of method TF-IDF. The process of retrieval is a process of calculating the slope of the query against the document, the calculation of the similarity using concept vector space model by finding the value of cosine similarity. Based on the analysis and implementation in the build of search system in the news. The quick method of search can be built using vector space model. The system build by this method of vector is able to display a results of search that relevant accordance with the query in the user input. Keywords: term frequency - inverse document frequency, vector space model, search a news of Indonesian language, indexing, retrieval.