ANALISIS SENTIMENT OPINI PENGGUNA TWITTER TERKAIT METAVERSE MENGGUNAKAN METODE LEXICON-BASED

PRATAMA, NUGRAHA ARDINATA (2022) ANALISIS SENTIMENT OPINI PENGGUNA TWITTER TERKAIT METAVERSE MENGGUNAKAN METODE LEXICON-BASED. S1 thesis, Universitas Mercu Buana.

[img]
Preview
 Text (HAL COVER)
01 Cover.pdf
Download (762kB) | Preview
[img] Text (ABSTRAK)
02 Abstrak.pdf
Restricted to Registered users only
Download (24kB)
[img] Text (BAB 1)
03 Bab 1.pdf
Restricted to Registered users only
Download (104kB)
[img] Text (BAB 2)
04 Bab 2.pdf
Restricted to Registered users only
Download (25kB)
[img] Text (BAB 3)
05 Bab 3.pdf
Restricted to Registered users only
Download (36kB)
[img] Text (BAB 4)
06 Bab 4.pdf
Restricted to Registered users only
Download (27kB)
[img] Text (BAB 5)
07 Bab 5.pdf
Restricted to Registered users only
Download (218kB)
[img] Text (BAB 6)
08 Bab 6.pdf
Restricted to Registered users only
Download (28kB)
[img] Text (DAFTAR PUSTAKA)
09 Daftar Pustaka.pdf
Restricted to Registered users only
Download (86kB)
[img] Text (LAMPIRAN)
10 Lampiran.pdf
Restricted to Registered users only
Download (203kB)

Abstract

In the current era, the development of the internet and the digital world is increasingly rapid, now many technology and digital companies have developed the latest features and solutions related to the future of using the internet. Internet technology has now entered into all sectors from business, education, and daily life. Now, a technology called Metaverse has emerged, this technology is being manipulated by Mark Zuckerberg, Facebook's social media developer. On October 29, 2021 Mark announced that Facebook would change its name to Meta and would also invest heavily in Metaverse technology. In general, metaverse is like a 3d-based simulation world like the game we often play, namely The Sims, this is what makes the Metaverse project invite pros and cons from the community. Twitter is one of the social media that is a place for people to discuss this Metaverse, arguing with each other in viewing this metaverse. The purpose of this study is to analyze the sentiment of public opinion on Twitter into 3 classifications of positive, neutral, and negative and to measure the level of accuracy of the lexicon based method manually. The method that will be used is the lexicon based method where the sentences in the dataset are calculated for their polarity level. Based on the results of research that has been done from 1227 data, it was found that 883 neutral data, 305 positive data, 89 negative data and an accuracy of 76%. Key words: analisis sentiment,metaverse,Lexicon Based Pada era sekarang, perkembangan dunia internet dan dunia digital kian hari kian pesat, kini sudah banyak perusahaan perusahaan teknologi dan digital yang mengembangkan fitur fitur maupun solusi solusi terbaru terkait masa depan menggunakan internet. Teknologi internet kini telah masuk kedalam semua sektor mulai bisnis, Pendidikan, maupun kehidupan sehari-hari. Kini, telah muncul teknologi Bernama Metaverse, teknologi ini di siasati oleh Mark Zuckerberg, pengembang media sosial Facebook. Pada 29 Oktober 2021 Mark mengumumkan bahwa Facebook akan mengganti Namanya dengan nama Meta dan juga akan berinvestasi secara besar-besaran untuk teknologi Metaverse. Secara umum, metaverse adalah seperti dunia simulasi berbasis 3d seperti permainan yang sering kita mainkan yaitu The Sims, hal inilah yang membuat proyek Metaverse mengundang pro dan kontra dari masyarakat. Twitter adalah salah satu media sosial yang menjadi lahan untuk masyarakat membahas tentang Metaverse ini, saling beradu argument satu sama lain dalam memandang metaverse ini. Tujuan dari penelitian ini adalah melakukan analisis sentimen terhadap opini masyarakat di Twitter menjadi 3 klasifikasi positif, netral, dan negatif serta mengukur tingkat akurasi dari metode lexicon based secara manual. Metode yang akan digunakan adalah metode lexicon based dimana kalimat yang ada didalam dataset dihitung tingkat polaritasnya. Berdasarkan hasil penelitian yang telah dilakukan dari 1227 data didapatkan bahwa 883 data netral, 305 data positif, 89 data negatif dan mendapatkan akurasi sebesar 76%. Kata kunci: analisis sentiment,metaverse,Lexicon Based

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 22 048
NIM/NIDN Creators: 41518010134
Uncontrolled Keywords: analisis sentiment,metaverse,Lexicon Based
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan > 025.3 Bibliographic Analysis and Control/Bibliografi Analisis dan Kontrol Perpustakaan
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan > 025.4 Subject Analysis and Control/Subjek Analisis dan Kontrol Perpustakaan
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: LUTHFIAH RAISYA ARDANI
Date Deposited: 16 Sep 2022 08:33
Last Modified: 19 Sep 2022 02:49
URI: http://repository.mercubuana.ac.id/id/eprint/69148

Actions (login required)

View Item View Item
UMB Repository is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.