Daftar Isi: ANALISIS SENTIMEN REVIEW BUKU BAHASA INDONESIA DI SITUS GOODREADS MENGGUNAKAN METODE RECURRENT NEURAL NETWORK

Main Authors:	APRIANI, TIARA WINDRI, Fachrurrozi, M., Yusliani, Novi
Format:	Thesis NonPeerReviewed Book
Bahasa:	ind
Terbitan:	, 2018
Subjects:	T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Online Access:	http://repository.unsri.ac.id/11448/1/RAMA_%2055201_%2009021381320018.pdf http://repository.unsri.ac.id/11448/2/RAMA_%2055201_%2009021381320018_0222058001_0008118205_01_front_ref.pdf http://repository.unsri.ac.id/11448/3/RAMA_%2055201_%2009021381320018_0222058001_0008118205_02.pdf http://repository.unsri.ac.id/11448/4/RAMA_%2055201_%2009021381320018_0222058001_0008118205_03.pdf http://repository.unsri.ac.id/11448/5/RAMA_%2055201_%2009021381320018_0222058001_0008118205_04.pdf http://repository.unsri.ac.id/11448/6/RAMA_%2055201_%2009021381320018_0222058001_0008118205_05.pdf http://repository.unsri.ac.id/11448/7/RAMA_%2055201_%2009021381320018_0222058001_0008118205_06_ref.pdf http://repository.unsri.ac.id/11448/8/RAMA_%2055201_%2009021381320018_0222058001_0008118205_07_lamp.pdf http://repository.unsri.ac.id/11448/

Daftar Isi:

Pembangunan perangkat lunak Analisis Sentimen Review Buku Berbahasa Indonesia di situs Goodreads yang diimplementasikan menggunakan Recurrent Neural Network berhasil dilakukan. Nilai rata-rata akurasi yang didapatkan dari Analisis Sentimen Review Buku Berbahasa Indonesia di situs Goodreads menggunakan Recurrent Neural Network mendapatkan nilai recall 76.1%, precision 73.3%, dan f-measure 74.67%, dan akurasi 73.3%.