JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi)
Vol 6, No 1 (2018): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI

OPINION MINING UNTUK ULASAN PRODUK DENGAN KLASIFIKASI NAIVE BAYES

Albert Jeremy (Unknown)
Viny Christanti M (Unknown)
Bagus Mulyawan (Unknown)



Article Info

Publish Date
12 Nov 2018

Abstract

Nowadays, micro blogs have become the most used tools for users to share many things: from just updating things to telling their conditions or thoughts. Some popular micro blogs mostly used to give comments and opinions are facebook, instagram, and twitter. Twitter has 259 million active users each month as for January until April 2017. This made twitter one of the best micro blogs to know the most updated opinions.The system uses Naive Bayes Classification to classify opinions about smartphone and computer from twitter. The sentiments are divided to positive, neutral, and negative. After that, Confusion Matrix is used to evaluate the algorithm and count the accuracy. Naive Bayes Classification gives 77.7% accuracy for Unigram, 50.7% for Bigram, and 31.7% for Trigram

Copyrights © 2018






Journal Info

Abbrev

jiksi

Publisher

Subject

Computer Science & IT Mathematics Other

Description

Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) diterbitkan oleh Fakultas Teknologi Informasi Universitas Tarumanagara (FTI Untar) Jakarta sebagai media publikasi karya ilmiah mahasiswa program studi Teknik Informatika dan Sistem Informasi FTI Untar. Karya-karya ilmiah yang dihasilkan berupa hasil ...