Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Pseudocode Journal of Electrical Engineering and Computer (JEECOM)
Saiful Bahri
Universitas AMIKOM Yogyakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Pseudocode

 1 
ANALISIS SENTIMEN LPDP (LEMBAGA PENGELOLA DANA PENDIDIKAN) PADA MEDIA SOSIAL TWITTER Samuel Adhi Bagaskoro; Atin Hasanah; Saiful Bahri; Ema Utami; Ainul Yaqin
Jurnal Pseudocode Vol 10 No 2 (2023): Volume 10 Nomor 2 September 2023
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.10.2.65-73

Abstract

LPDP Scholarship (Education Fund Management Institution) is the most sought after by prospective students who want to continue their studies in the country, especially for those who want to continue their studies abroad. Recently, LPDP experienced problems related to students who received LPDP scholarships but did not return to Indonesia in accordance with the rules that have been stated. Starting from the incident on twitter, the topic of "LPDP" became a trending topic among twitter users. So it is our concern to find out and analyze public opinion through this twitter social media. By comparing the results of two methods, namely Support Vector Machine (SVM) and Naïve Bayes in classifying the twitter sentiment. As well as the calculation of accuracy using the Confusion Matrix, there are as many as 1000 tweets result from crawling. This research resulted in a classification that uses the Vader Lexicon Library built by NLTK, the Naïve Bayes method and Support Vector Machine (SVM) has not yet reached an accuracy rate of 70%. In contrast, the Support Vector Machine (SVM) method that uses the Vader Lexicon Library from VaderSentiment achieves an accuracy rate of 90%, with a ratio of 90:10 (training data: test data). Keywords: LPDP, Naïve Bayes, Sentiment Analysis, Support Vector Machine (SVM), Vader Lexicon.
Co-Authors Ainul Yaqin Andi Sunyoto Atin Hasanah Ema Utami Mei P. Kurniawan Samuel Adhi Bagaskoro