ANALISIS EMOSI PADA TEKS BAHASA INDONESIA DENGAN METODE NEIGHBOUR-WEIGHTED K-NEAREST NEIGHBOUR

Kevin Kurniawan H., Viny Christanti Mawardi

Abstract


Currently, the electronic media in the form of text became one of the primary of communication, so communication indirectly be a form of communication that is often used. Communication with text can not deliver emotions directly and can be misunderstood because of the perception of words so it needs application to help determine emotions in text communication. Analysis of emotions using Neighbour-Weighted K-Nearest Neighbour to classify the uneven distribution of data. The accuracy of emotion analysis system in the Indonesian language text by using Neighbour-Weighted K-Nearest Neighbour is about 76%.

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