Design and Implementation of Tourism News Information Retrieval System using Modified Cosine Similarity

Abstract

Technological developments cannot be denied a very meaningful impact on human life so that what was previously done traditionally is now completely digital, for example conventional news media which has been transformed into an online news portal so that it can still reach its readers. Online news portals provide a lot of up-to-date information, including tourism news, which is an industry that continues to grow and has the opportunity to create new jobs for the community. Currently, to search for tourism news, people only need to type a keyword (query) in the search engine which will then display the latest news about tourism. However, not all tourism news displayed matches what they are looking for, so readers have to re-check which takes a lot of time. Therefore, a tourism news retrieval system that can display the most relevant tourism news to the query is proposed. The Modified Cosine method shows good results in document clustering to bring the inter-cluster distance closer. This study uses the Modified Cosine method and TF-IDF weighting schema to determine the value of precision, recall, and f-measure in calculating the similarity of the query to tourism news documents. The system has been tested using 3 types of queries, with 5 different words each. The test results show that Modified Cosine method obtained best precision value in the test using 5 words in the query and the F-Measure value and the best recall on the 3 words test in query.