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Sitepu, Marheni
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Computer Science & IT Economics, Econometrics & Finance

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ANALISIS SENTIMEN TERHADAP APLIKASI LINKAJA MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Sitepu, Marheni; Yohanna, Margaretha; Manurung, Samuel Van Basten H.
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 1 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No1.pp44-50

Abstract

Electronic money is increasing, causing more and more service innovations to emerge. People carry out online transactions using electronic technology, or Fintech. The fintechs widely used today are e-wallets or digital wallets such as Dana, Ovo, LinkAja, etc. In this research, LinkAja as a fintech application will be analyzed using 100 review data samples and summarized into two classes: positive and negative. This research was carried out using the Naïve Bayes Classifier classification method. Sentiment analysis of reviews on the LinkAja application obtained results of 75% accuracy, 83% Precision, 75% Recall, and 73% F1_score.
ANALISIS SENTIMEN TERHADAP APLIKASI LINKAJA MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Sitepu, Marheni; Yohanna, Margaretha; Manurung, Samuel Van Basten H.
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 1 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No1.pp44-50

Abstract

Electronic money is increasing, causing more and more service innovations to emerge. People carry out online transactions using electronic technology, or Fintech. The fintechs widely used today are e-wallets or digital wallets such as Dana, Ovo, LinkAja, etc. In this research, LinkAja as a fintech application will be analyzed using 100 review data samples and summarized into two classes: positive and negative. This research was carried out using the Naïve Bayes Classifier classification method. Sentiment analysis of reviews on the LinkAja application obtained results of 75% accuracy, 83% Precision, 75% Recall, and 73% F1_score.
Co-Authors Manurung, Samuel Van Basten H. Yohanna, Margaretha