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All Journal JISKa (Jurnal Informatika Sunan Kalijaga)
Tri Andika Maulana
Institut Teknologi Sepuluh Nopember
Computer Science & IT Electrical & Electronics Engineering Library & Information Science

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Perbandingan Algoritma Klasifikasi Sentimen Twitter Terhadap Insiden Kebocoran Data Tokopedia Nadhif Ikbar Wibowo; Tri Andika Maulana; Hamzah Muhammad; Nur Aini Rakhmawati
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 2 (2021): Mei 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.329 KB) | DOI: 10.14421/jiska.2021.6.2.120-129

Abstract

Public responses, posted on Twitter reacting to the Tokopedia data leak incident, were used as a data set to compare the performance of three different classifiers, trained using supervised learning modeling, to classify sentiment on the text. All tweets were classified into either positive, negative, or neutral classes. This study compares the performance of Random Forest, Support-Vector Machine, and Logistic Regression classifier. Data was scraped automatically and used to evaluate several models; the SVM-based model has the highest f1-score 0.503583. SVM is the best performing classifier.
Co-Authors Hamzah Muhammad Nadhif Ikbar Wibowo Nur Aini Rakhmawati