eprintid: 43363
rev_number: 10
eprint_status: archive
userid: 12316
dir: disk0/00/04/33/63
datestamp: 2021-08-18 03:08:12
lastmod: 2021-08-18 03:08:12
status_changed: 2021-08-18 03:08:12
type: thesis
metadata_visibility: show
creators_name: Inaratul Mahbubah, NIM.: 16650069
title: ANALISSIS SENTIMEN KEPUASAN PELANGGAN ONLINE SHOP
MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER DAN K-NEAREST 
NEIGHBOR (Studi Kasus : Twitter Resmi Shopeecare)
ispublished: pub
subjects: TB
divisions: jur_tinf
full_text_status: restricted
keywords: Sentiment analysis, Naïve Bayes Classifier, K-NN (K-Nearest Neighbor)
note: Pembimbing : Muhammad Didik Rohmad Wahyudi, S.T., M.T
abstract: Shopee is one of the mostly used online marketplace in Indonesia. People around the world 
are most likely to buy products through online marketplace nowadays, including Indonesians. It 
happens because the citizens find online shopping is easier and more practical. Other than that, 
some people think the products are cheaper and the availability of many discounted prices given 
by the online stores. 
In this research, sentiment analysis was carried out using 1015 tweets as training data and 480 
tweets as testing data. The data was tested using the Naïve Byes Classifier method and K-NN using 
the confusion matrix. Data tested using the Naïve Bayes Classifier using confusion matrix obtains 
an accuracy rate of 86.27% with a split ratio of 90:10, an accuracy rate of 88.17% with a split 
ratio of 80:20, and an accuracy rate of 85.90% with a split ratio of 70:30. Whilst the data 
processed using K-NN using a configuration matrix obtains an accuracy rate of 84.31% with a 
split ratio of 90:10, an accuracy rate of 87.68% with a split ratio of 80:20, and an accuracy rate 
of 87.21% with a ratio split 70:30. The results of the implementation of the 480 new data tweets 
obtained on the Naïve Bayes Classifier are 25.6% positive data and 74.4% negative data. 
Meanwhile, the implementation of K-NN are 40.2% positive data and 59.8% negative data.
date: 2020-12-22
date_type: published
pages: 90
institution: UIN SUNAN KALIJAGA YOGYAKARTA
department: FAKULTAS SAINS DAN TEKNOLOGI
thesis_type: skripsi
thesis_name: other
citation:   Inaratul Mahbubah, NIM.: 16650069  (2020) ANALISSIS SENTIMEN KEPUASAN PELANGGAN ONLINE SHOP MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER DAN K-NEAREST NEIGHBOR (Studi Kasus : Twitter Resmi Shopeecare).  Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.   
document_url: https://digilib.uin-suka.ac.id/id/eprint/43363/1/16650069_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
document_url: https://digilib.uin-suka.ac.id/id/eprint/43363/2/16650069_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf