Peringkasan Multi-Dokumen Berbasis Clustering pada Sistem Temu Kembali Berita Online Menggunakan Metode K-Means - Amalia Kusuma Akaresti; Mochammad Ali Fauzi; Fitra Abdurrachman Bachtiar (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
The growing number of online news sites resulted in an explosion of information and information redundancy occurred. On this issue it takes the search engine to make it easier for users to find information, but users still have to read it one by one, therefore it needs also a summary system. Therefore a summary system is required to facilitate Internet users avoid getting the same information from different sources. In this study, multi-document clustering based on online news retrieval system using K-Means method. The process of searching system using Cosine Similarity method and on the summary using K-Means Clustering method. The results show that the optimum results in the recall system are Recall 71%, Presicion 65.82%, F-Measure 66.35% and on Recall system of Recall 37.3%, Presicion 18%, F-Measure 19.2%.