ANALISIS SENTIMEN TERHADAP PENGGUNA QRIS PADA APLIKASI GOPAY PADA ULASAN GOOGLE PLAY STORE DENGAN METODE SUPPORT VECTOR MACHINE

ARITONANG, ERLINDA SISTIA (2025) ANALISIS SENTIMEN TERHADAP PENGGUNA QRIS PADA APLIKASI GOPAY PADA ULASAN GOOGLE PLAY STORE DENGAN METODE SUPPORT VECTOR MACHINE. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

This study aims to analyze user sentiment towards the use of QRIS on the GoPay application through reviews available on the Google Play Store. The data used consists of over 2.000 user reviews, which were processed through several stages: preprocessing, manual labeling, and feature extraction using the TF-IDF method. The main algorithm used for sentiment classification is Support Vector Machine (SVM), which is compared with Naive Bayes and Decision Tree algorithms. Evaluation was conducted using accuracy, precision, recall, and F1- score metrics. The results show that the SVM algorithm provides the best performance in classifying user opinions into positive, negative, and netral sentiments. This research is expected to serve as a reference for the development of public opinion analysis systems based on digital payment techonologies such as QRIS, Keywords: QRIS,GoPay, Sentiment Analysis, Support Vector Machine, Naive Bayes, Decision Tree, TF – IDF, Google Play Store. Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap penggunaan QRIS pada aplikasi GoPay melalui ulasan yang tersedia di Google Play Store. Data yang digunakan berupa 2000 lebih ulasan pengguna yang kemudian diproses melalui tahap preprocessing,pelabelan secraa manual, serta ekstraksi fitur menggunakan metode TF – IDF. Algoritma utama yang digunakan dalam klasifikasi sentimen ini adalah support Vector Machine (SVM), dengan perbandingan terhadap algoritma Naive Bayes dan Decision Tree. Evaluasi dilakukan menggunakan metrik akurasi, presisi,recall, dan f1-score. Hasil Penelitian menunjukkan bahwa algoritma SVM memberikan performa terbaik dalam mengklasifikasikan opini pengguna menjadi sentimen positif, negatif, dan netral. Penelitian ini diharapkan dapat menjadi acuan dalam pengembangan sistem analisis opini publik berbasis teknologi pembayaran digital seperti QRIS. Kata Kunci: QRIS, GoPay, Analisis Sentimen. SVM, Naive Bayes, Decision Tree, TF-IDF-Google Play Store.

Item Type:	Thesis (S1)
Call Number CD:	FIK/SI. 25 088
NIM/NIDN Creators:	41820010065
Uncontrolled Keywords:	QRIS, GoPay, Analisis Sentimen. SVM, Naive Bayes, Decision Tree, TF-IDF-Google Play Store.
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data > 005.5 General Purpose Application Programs/Program Aplikasi dengan Kegunaan Khusus 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 > 025.1 Administration and Library Management/Administrasi dan Manajemen Perpustakaan > 025.11 Finance/Keuangan 100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 153 Conscious Mental Process and Intelligence/Intelegensia, Kecerdasan Proses Intelektual dan Mental > 153.1 Memory and Learning/Memori dan Pembelajaran > 153.15 Learning/Pembelajaran 600 Technology/Teknologi > 600. Technology/Teknologi
Divisions:	Fakultas Ilmu Komputer > Sistem Informasi
Depositing User:	khalimah
Date Deposited:	16 Sep 2025 03:58
Last Modified:	16 Sep 2025 03:58
URI:	http://repository.mercubuana.ac.id/id/eprint/97925

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