(MIB - S3) - Nugroho, Hasan [2024-04-23]

Hasan, Firman Noor (2024) (MIB - S3) - Nugroho, Hasan [2024-04-23]. MIB: Media Informatika Budidarma, 8 (2). pp. 843-853. ISSN 2548-8368

[thumbnail of 1.  Cover.pdf]
Preview
Text
1. Cover.pdf

Download (83kB) | Preview
[thumbnail of 2.  Editorial Team.pdf]
Preview
Text
2. Editorial Team.pdf

Download (277kB) | Preview
[thumbnail of 3.  Daftar Isi.pdf]
Preview
Text
3. Daftar Isi.pdf

Download (292kB) | Preview
[thumbnail of 4.  Artikel.pdf]
Preview
Text
4. Artikel.pdf

Download (1MB) | Preview
[thumbnail of 5.  Bukti Hasil Cek Turnitin.pdf]
Preview
Text
5. Bukti Hasil Cek Turnitin.pdf

Download (2MB) | Preview
[thumbnail of 6.  LOA - Aprilianto, Hasan.pdf]
Preview
Text
6. LOA - Aprilianto, Hasan.pdf

Download (174kB) | Preview
Official URL: https://ejurnal.stmik-budidarma.ac.id/index.php/mi...

Abstract

Human daily activities inevitably produce waste, which negatively impacts environmental balance due to the bad habit of indiscriminately disposing of waste. As a result of this issue, there is a youth community named Pandawara Group that wants to help clean up trash on Sukabumi Beach. However, their initiative faced rejection from the local village chief and youth organization, sparking various opinions on social media platform X. Consequently, this research seeks to analyze public sentiment towards Pandawara Group's waste cleanup efforts at Sukabumi Beach using Support Vector Machine and Naïve Bayes methods. The objective is to gauge positive and negative sentiments and compare the accuracy of Support Vector Machine and Naïve Bayes. In this sentiment analysis using 2,339 datasets, the highest accuracy was achieved using the Support Vector Machine method at 91.67%, whereas the Naïve Bayes method only achieved 63.89%. Thus, it can be concluded that Support Vector Machine is superior in classifying sentiments regarding Pandawara Group's waste cleanup activities at Sukabumi Beach compared to Naïve Bayes.

Item Type: Article
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Teknik > Teknik Informatika
Depositing User: Mr Firman Noor Hasan
Date Deposited: 14 May 2024 02:46
Last Modified: 14 May 2024 02:46
URI: http://repository.uhamka.ac.id/id/eprint/34174

Actions (login required)

View Item View Item