KLASIFIKASI SENTIMEN PEMBELI BERDASARKAN LAYANAN SMS “SUARA KONSUMEN” TERHADAP PRODUK MENGGUNAKAN METODE K-NN
Abstract: Limited number of
characters in an SMS causes the use of words and the structure of solid and
compact but obviously become very important in presenting the content and
purpose of the sender of the SMS. This research studied how the use of SMS
classify structures and limited words to get the sentiment of an SMS service
"Suara Konsumen" through text mining approach. This study uses K-NN
algorithm in the classification, besides the K-NN algorithm of this study will
be weighted words using TF-IDF methods, Feature Selection in the selection of
words also Cosine Similiarity in measuring the degree of proximity between
documents. In determining the success, measured the accuracy of the documents
the trial and the results are very accurate with an average value of 89%
accuracy on the variation of K and Feature Selection.
Keywords: K-Nearest Neighbor,
Sentiment Analysist, Document Classification, Short Message Service, Cosine
Similiarity
Penulis: David Addiwijaya
Hanz, Budi Susanto, Lukas Chrisantyo
Kode Jurnal: jptinformatikadd150383
