 |
UPT. PERPUSTAKAAN
Universitas Esa Unggul
Kampus Emas UEU - Jakarta Barat
|
Phone |
: |
021-5674223, ext 282 |
Fax |
: |
|
E-mail |
: |
[email protected] |
Website |
: |
http://library.esaunggul.ac.id
|
Support (Customer Service) :
|
[email protected] |
|
|
Welcome..guys!
|
Have a problem with your access?
Please, contact our technical support below:
|
LIVE SUPPORT
 Astrid Chrisafi
|
! ATTENTION !
To facilitate the activation process, please fill out the member application form correctly and completely
Registration activation of our members will process up to max 24 hours (confirm by email). Please wait patiently
Still Confuse?
Please read our User Guide
|
|
UEU » Undergraduate Theses » Teknik Informatika Posted by [email protected] at 23/03/2021 11:12:44 • 1252 Views
PENERAPAN ALGORITMA MULTINOMIAL NA�VE BAYES PADA ANALISIS SENTIMEN TOPIK PERPAJAKAN BERBAHASA INDONESIA PADA MEDIA SOSIAL TWITTERCreated by :
WIDY ASTUTI ( 20160801297 )
Subject: | ALGORITMA MULTINOMIAL PERPAJAKAN | Alt. Subject : | MULTINOMIAL ALGORITHM TAXATION | Keyword: | Multinomial Na�ve Classifier Analisa Sentimen. Twitter Pajak |
Description:
Bayes pada Analisis Sentimen topik perpajakan berbahasa Indonesia pada data
media sosial Twitter. Manfaat penelitian ini adalah pengembangan Aplikasi monitoring
sentimen berbasis web yang dapat mendukung Direktorat Penyuluhan Pelayanan dan
Hubungan Masyarakat Direktorat Jenderal Pajak dalam melakukan monitoring sosial
media terkait topik perpajakan. Pengumpulan data pada penelitian ini dilakukan secara
kualitatif melalui wawancara dan studi literatur. Metode penelitian yang digunakan adalah
metode analisis dan metode perancangan. Metode analisis dilakukan dengan menganalisa
masalah dan implementasi.
Hasil penelitian dengan tingkat presisi 75,40%, Recall 74,95%, akurasi 76,33 %
dan F-Score 74,99%. Implementasi model klasifikasi kemudian diterapkan pada sejumlah
tweet yang menganduk kata �Insentif Pajak� dengan proses pengumpulan data dalam
rentang tanggal 20 sampai dengan 26 juni 2020. Hasil menunjukan klasifikasi sejumlah
9,6% tweet bersentimen positif, bersentimen negatif 9,8% tweet dan 80,6% tweet netral.
Total tweet berjumlah 2115 Tweet. Model kemudian diimplementasikan pada Aplikasi
monitoring berbasis web bernama ANSET (Analisa Sentimen Twitter).
Contributor | : |
- Imam Sutanto, S.Kom, M.Kom
| Date Create | : | 23/03/2021 | Type | : | Text | Format | : | PDF | Language | : | Indonesian | Identifier | : | UEU-Undergraduate-20160801297 | Collection ID | : | 20160801297 |
Source : Undergraduate Theses of Computer Sciences
Relation Collection: Fakultas Ilmu Komputer
Coverage : Civitas Akademika Universitas Esa Unggul
Rights : @perpustakaan Universitas Esa Unggul 2021
Publication URL : https://digilib.esaunggul.ac.id/penerapan-algoritma-multinomial-nave-bayes-pada-analisis-sentimen-topik-perpajakan-berbahasa-indonesia-pada-media-sosial-twitter-19435.html
[ Free Download - Free for All ]
UEU-Undergraduate-19435-COVER.Image.Marked.pdf - 169 KB UEU-Undergraduate-19435-HALAMAN PENGESAHAN.Image.Marked.pdf - 254 KB UEU-Undergraduate-19435-HALAMAN PERSETUJUAN PUBLIKASI.Image.Marked.pdf - 214 KB UEU-Undergraduate-19435-HALAMAN PERNYATAAN KEASLIAN.Image.Marked.pdf - 2159 KB UEU-Undergraduate-19435-ABSTRAK.Image.Marked.pdf - 216 KB UEU-Undergraduate-19435-KATA PENGANTAR.Image.Marked.pdf - 225 KB UEU-Undergraduate-19435-DAFTAR ISI.Image.Marked.pdf - 228 KB UEU-Undergraduate-19435-DAFTAR PUSTAKA.Image.Marked.pdf - 211 KB UEU-Undergraduate-19435-LAMPIRAN.Image.Marked.pdf - 2535 KB UEU-Undergraduate-19435-BAB1.Image.Marked.pdf - 260 KB
[ FullText Content - Please, register first ]
1. UEU-Undergraduate-19435-BAB2.Image.Marked.pdf - 1332 KB 2. UEU-Undergraduate-19435-BAB3.Image.Marked.pdf - 660 KB 3. UEU-Undergraduate-19435-BAB4.Image.Marked.pdf - 827 KB 4. UEU-Undergraduate-19435-BAB5.Image.Marked.pdf - 185 KB
10 Similar Document...
No similar subject found !
10 Related Document...
No related subject found !
|
POLLING

       
Visitors Today : 3
Total Visitor : 1970612
Hits Today : 122335
Total Hits : 190102605
Visitors Online: 1
Calculated since 16 May 2012
You are connected from 172.17.121.29 using Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; [email protected])
|