PERBANDINGAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE TERHADAP REVIEW APLIKASI BLU BY BCA DIGITAL

RAHMA, AFIFA VINA (2023) PERBANDINGAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE TERHADAP REVIEW APLIKASI BLU BY BCA DIGITAL. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Technology and the internet are growing rapidly nowadays, especially in the field of financial services. This change has been significant in the banking industry, with the increasing use of digital banking services. The value of electronic money transactions is also experiencing high growth, and surveys show that more and more people will use digital banking applications in the future. One example of a digital banking application is Blu by BCA. Many users write reviews about Blu on Google Play Store regarding Blu app's quality of service, experience and product. These reviews can be processed into important information to improve service quality and customer retention strategies by means of sentiment analysis. Sentiment analysis is performed to categorize reviews as positive or negative. Therefore, this research was conducted with the aim of knowing the subjectivity of public opinion or sentiment analysis using the Naïve Bayes (NB) algorithm and Support Vector Machine (SVM) using the lexicon-based method for labeling and using the TF-IDF method for word weighting. The results show that the SVM algorithm obtains the most accurate results of 93.48%% accuracy, 93.60%% precision, and 93.48%% recall. Meanwhile, the Naïve Bayes algorithm obtains an accuracy of 84.71%, a precision of 84.83%, and a recall of 84.73%. It can be concluded that SVM produces the best algorithm because it has the best accuracy rate of 93.48%. Keywords : Sentiment Analysis, Naïve Bayes, SVM, Blu Teknologi dan internet berkembang pesat pada zaman sekarang, terutama dalam bidang layanan keuangan. Perubahan ini telah signifikan dalam industri perbankan, dengan meningkatnya penggunaan layanan perbankan digital. Nilai transaksi uang elektronik juga mengalami pertumbuhan yang tinggi, dan survei menunjukkan bahwa semakin banyak orang akan menggunakan aplikasi perbankan digital di masa depan. Salah satu contoh aplikasi perbankan digital adalah Blu by BCA. Banyak pengguna yang menulis ulasan mengenai Blu di Google Play Store tentang kualitas layanan, pengalaman dan produk aplikasi Blu. Ulasan tersebut dapat diolah menjadi suatu informasi yang penting untuk meningkatkan kualitas layanan dan strategi mempertahankan pelanggan dengan cara analisis sentimen. Analisis sentimen dilakukan untuk mengelompokkan ulasan sebagai positif atau negatif. Oleh karena itu, penelitian ini dilakukan bertujuan untuk mengetahui subjektivitas opini masyarakat atau analisis sentimen dengan menggunakan algoritma Naïve Bayes (NB) dan Support Vector Machine (SVM) dengan menggunakan metode lexicon-based untuk pelabelannya serta menggunakan metode TF-IDF dalam pembobotan kata. Hasil menunjukkan bahwa pada algoritma SVM mendapatkan hasil akurasi yang paling akurat sebesar 93,48%%, precision sebesar 93,60%%, dan recall sebesar 93,48%%. Sedangkan algoritma Naïve Bayes mendapatkan akurasi sebesar 84,71% precision sebesar 84,83%%, dan recall sebesar 84,73%%. Hal ini dapat disimpulkan bahwa SVM menghasilkan algoritma terbaik karena memiliki tingkat akurasi terbaik yaitu 93,48%. Kata Kunci : Analisa Sentimen, Naïve Bayes, SVM, Blu

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 23 114
NIM/NIDN Creators:	41519010176
Uncontrolled Keywords:	Analisa Sentimen, Naïve Bayes, SVM, Blu
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 > 003 Systems/Sistem-sistem 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 > 003 Systems/Sistem-sistem > 003.5 Computer Modeling and Simulation/Model dan Simulasi Komputer 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 > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 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 > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.1 General Works on Specific Types of Computers/Karya Umum tentang Tipe-tipe Khusus Komputer
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	CALVIN PRASETYO
Date Deposited:	05 Oct 2023 02:57
Last Modified:	05 Oct 2023 03:56
URI:	http://repository.mercubuana.ac.id/id/eprint/82011

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