Comparison of Sentiment Analysis against Digital Payment “T-cash and Go-pay” in Social Media Using Orange Data Mining

Perbandingan Analisis Sentimen Terhadap Digital Payment “ T-cash dan Go-pay” Di Sosial Media Menggunakan Orange Data Mining

Authors

  • Novita Anggraini Universitas Bina Darma, Indonesia
  • Heri Suroyo Universitas Bina Darma, Indonesia
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DOI:

https://doi.org/10.33557/journalisi.v1i2.21

Keywords:

Analisis Sentimen, Vader, Orange Data Mining, Go-pay, Tcash

Abstract

Saat ini pembicaraan publik di sosial media menjadi salah satu hal menarik untuk diteliti. Dari topik pembicaraan itu menghasilkan komentar yang sebagian besar mengandung opini sentimen. Penelitian ini mencoba menganalisis komentar dengan metode analisis vader, yaitu metode analisis lexicon-based berbasis rule-based sentiment analysis. Vader akan menganalisis text berdasarkan lexicon (a library) yang menghasilkan class sentimen berupa  positif, negatif, dan neutral dengan tambahan skor total atau compound (combined score). Penelitian ini memanfaatkan Prepocess text yang meliputi transformation, tokenization, normalization, dan filtering yang bertujuan agar text bisa dianalisis oleh Orange Data Mining guna mendapat perbandingan analisis sentimen terhadap T-cash dan Go-pay di sosial media. Dari penelitian yang dilakukan mendapat kesimpulan bahwa T-cash memiliki nilai sentimen positif lebih tinggi dari pada Go-pay dan memiliki sentimen negatif yang lebih rendah dari pada Go-pay. Namun persamaanya T-cash dan Go-pay memiliki kesamaan pola grafik dimana sentimen terbesar adalah neutral, diikuti oleh positif, dan terakhir adalah negative.

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Published

2019-09-02

Issue

Vol. 1 No. 2 (2019): Journal of Information Systems and Informatics

Section

Articles

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How to Cite

[1]
N. Anggraini and H. Suroyo, “Comparison of Sentiment Analysis against Digital Payment “T-cash and Go-pay” in Social Media Using Orange Data Mining : Perbandingan Analisis Sentimen Terhadap Digital Payment ‘ T-cash dan Go-pay’ Di Sosial Media Menggunakan Orange Data Mining”, journalisi, vol. 1, no. 2, pp. 152–163, Sep. 2019, doi: 10.33557/journalisi.v1i2.21.

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