Implementasi Metode Support Vector Machine (SVM) pada Model Prediksi Rating Obat Berdasarkan Ulasan Pasien

Authors

  • Wisnu Jayanata
  • Isman Kurniawan

DOI:

https://doi.org/10.25124/logic.v1i1.6410

Keywords:

analisis sentimen, Support Vector Machine, TF-IDF, ulasan, obat

Abstract

Pesatnya perkembangan internet dan media sosial mengakibatkan membaca ulasan sebelum membeli suatu produk, terutama produk obat menjadi hal yang lumrah. Namun, jumlah ulasan yang banyak dan tersebar mengakibatkan kesulitan dalam melakukan penilaian kualitas produk obat. Oleh karena itu, sistem yang dapat membantu pelanggan dalam menghadapi kendala ini sangat dibutuhkan. Pada pemodelan sistem, digunakan TF-IDF untuk mereduksi fitur dan Support Vector Machine sebagai metode klasifikasi. Dilakukan puka Hyperparameter Tuning untuk meningkatkan performa sistem. Pada penelitian ini didapat bahwa polynomial merupakan kernel SVM yang paling optimal untuk memprediksi rating obat berdasarkan ulasan pasien dengan akurasi mencapai 75.00% dan f-1 score sebesar 74.23%.

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Published

2023-09-29

Issue

Vol. 1 No. 1 (2023): September 2023

Section

Articles

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