Analisis Sentimen Pelanggan Restoran Menggunakan Algoritma Multinomial Logistic Regression

Authors

  • Hajrianti Hajrianti Universitas Sulawesi Barat, Majene, Sulawesi Barat, Indonesia
  • Heliawati Hamrul Universitas Sulawesi Barat, Majene, Sulawesi Barat, Indonesia
  • A. Amirul Asnan Cirua Universitas Sulawesi Barat, Majene, Sulawesi Barat, Indonesia

DOI:

https://doi.org/10.62411/tc.v25i1.15532

Abstract

Industri kuliner di Indonesia terus mengalami perkembangan pesat, termasuk dengan hadirnya merek nasional seperti Mie Gacoan yang baru membuka cabang di Sulawesi Barat Mamuju. Kehadiran restoran tersebut memunculkan beragam opini dari masyarakat yang disampaikan melalui ulasan pelanggan. Penelitian ini bertujuan untuk melakukan analisis sentimen pelanggan terkait layanan restoran dengan penerapan algoritma Multinomial Logistic Regression. Data dikumpulkan melalui dua sumber, yaitu ulasan pelanggan dari scraping Google Maps dan kuesioner, dengan total sebanyak 773 data ulasan yang melalui tahap preprocessing teks dan pembobotan TF-IDF. Penelitian ini juga menerapkan pendekatan Explainable AI dengan metode Local Interpretable Model-agnostic Explanations (LIME) guna memperjelas kata-kata yang paling berpengaruh terhadap hasil klasifikasi model. Berdasarkan hasil pengujian, algoritma Multinomial Logistic Regression mampu memberikan performa klasifikasi dengan akurasi mencapai 86,5%, presisi 86,3%, recall 86,5%, dan F1-score 85,8% dalam mengidentifikasi opini pelanggan restoran. Temuan ini menunjukkan bahwa metode berbasis Machine Learning dan Explainable AI dapat memberikan analisis sentimen terhadap persepsi pelanggan, sehingga menjadi referensi penting bagi pengambilan keputusan strategis dalam peningkatan kualitas layanan. Kata kunci - Sentimen Pelanggan, Multinomial Logistic Regression, TF-IDF, Explainable AI, LIME

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Published

2026-02-26

Issue

Vol. 25 No. 1 (2026): February 2026

Section

Articles

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Copyright (c) 2026 Hajrianti Hajrianti, Heliawati Hamrul, A. Amirul Asnan Cirua

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