Analisis Sentimen Ulasan Pengguna Aplikasi Penjualan Pulsa Menggunakan Algoritma Naïve Bayes Classifier

Penulis

  • Azis Syafi'i Universitas Sultan Syarif Kasim Riau
  • M. Afdal Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Eki Saputra Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Rice Novita Universitas Islam Negeri Sultan Syarif Kasim Riau

DOI:

https://doi.org/10.32493/jtsi.v7i3.41364

Kata Kunci:

Analisis Sentimen; Aplikasi Penjualan Pulsa; DigiPOS; Naïve Bayes Classifier (NBC); Tetra Pulsa; Orderkuota

Abstrak

Terdapat banyak aplikasi penjualan pulsa yang umumnya digunakan oleh outlet atau konter, seperti DigiPOS, Tetra Pulsa, dan Orderkuota. Namun, terdapat permasalahan umum pada aplikasi tersebut seperti harga yang mulai kurang kompetitif, penggunaan yang sulit, transaksi yang sering gagal, keamanan, layanan dan lainnya. Untuk itu, penelitian ini menganalisis sentimen ulasan pengguna untuk mengidentifikasi kelebihan dan kekurangan aplikasi tersebut, dengan tujuan membantu pengembang meningkatkan layanan dan memberi panduan bagi agen dalam memilih aplikasi yang tepat. Algoritma NBC diusulkan untuk digunakan pada klasifikasi sentimen. Hasil analisis menunjukkan dominasi sentimen positif pada semua aplikasi, dengan Tetra Pulsa memiliki sentimen positif tertinggi (97.10%), diikuti oleh Orderkuota (84.40%) dan DigiPOS (64.00%). Kemudian hasil implementasi algoritma NBC mempu melakukan klasifikasi sentimen dengan baik. Aplikasi Tetra Pulsa memiliki akurasi 97.10%, Orderkuota 92.39%, dan DigiPOS 91.10%. Hasil penelitian ini dapat pertimbangan untuk melakukan evaluasi dan peningkatan aplikasi, sehingga dapat memberikan layanan yang lebih baik kepada pengguna aplikasi penjualan pulsa.

Referensi

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Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 Juli 2024

Unduhan

Diterbitkan

2024-07-31

Cara Mengutip

Syafi'i, A., Afdal, M., Saputra, E., & Novita, R. (2024). Analisis Sentimen Ulasan Pengguna Aplikasi Penjualan Pulsa Menggunakan Algoritma Naïve Bayes Classifier. Jurnal Teknologi Sistem Informasi Dan Aplikasi, 7(3), 1300–1308. https://doi.org/10.32493/jtsi.v7i3.41364

Terbitan

Vol 7 No 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi

Bagian

Article

Lisensi

Hak Cipta (c) 2024 Azis Syafi'i, M. Afdal, Eki Saputra, Rice Novita

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