Implementation of the common phrase index method on the phrase query for information retrieval

As the development of technology, the process of finding information on the news text is easy, because the text of the news is not only distributed in print media, such as newspapers, but also in electronic media that can be accessed using the search engine. In the process of finding relevant documents on the search engine, a phrase often used as a query. The number of words that make up the phrase query and their position obviously affect the relevance of the document produced. As a result, the accuracy of the information obtained will be affected. Based on the outlined problem, the purpose of this research was to analyze the implementation of the common phrase index method on information retrieval. This research will be conducted in English news text and implemented on a prototype to determine the relevance level of the documents produced. The system is built with the stages of pre-processing, indexing, term weighting calculation, and cosine similarity calculation. Then the system will display the document search results in a sequence, based on the cosine similarity. Furthermore, system testing will be conducted using 100 documents and 20 queries. That result is then used for the evaluation stage. First, determine the relevant documents using kappa statistic calculation. Second, determine the system success rate using precision, recall, and F-measure calculation. In this research, the result of kappa statistic calculation was 0.71, so that the relevant documents are eligible for the system evaluation. Then the calculation of precision, recall, and F-measure produces precision of 0.37, recall of 0.50, and F-measure of 0.43. From this result can be said that the success rate of the system to produce relevant documents is low.