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Analisis Sentimen Ulasan pada Gojek Menggunakan Metode Naive Bayes

Authors

  • Putri Yuniar Universitas Negeri Yogyakarta
  • Kismiantini

DOI:

https://doi.org/10.29313/statistika.v23i2.2353

Keywords:

Gojek, Analisis Sentimen, Naïve Bayes Classifier, Asosiasi Teks

Abstract

Abstrak

Gojek merupakan layanan transportasi online yang banyak digunakan di Indonesia. Penting bagi perusahaan untuk memahami persepsi masyarakat terhadap kualitas pelayanan dan produk yang ditawarkan. Namun, sulit untuk memantau banyaknya pendapat masyarakat untuk diproses secara manual. Tujuan dari penelitian ini yaitu mengklasifikasikan ulasan pada aplikasi Gojek dan menganalisis asosiasi kata dari hasil klasifikasi untuk mengetahui topik yang banyak dibicarakan dengan menggunakan data dari halaman Google Play. Beberapa tahapan yang dilakukan dalam analisis sentimen penelitian ini diantaranya yaitu pengumpulan data, preprocessing, perhitungan skor sentimen, pelabelan kelas sentimen, dan pengklasifikasian data dengan metode Naïve Bayes Classifier serta dilakukan asosiasi teks. Metode Naïve Bayes Classifier yaitu metode klasifikasi yang sederhana namun menghasilkan tingkat akurasi yang tinggi. Hasil penelitian dari data yang dikumpulkan pada 1-31 Januari 2023 dengan total sebanyak 4.198 ulasan, cenderung memiliki sentimen positif. Penelitian menggunakan metode Naïve Bayes Classifier dengan 3 rasio pembagian data training dan data testing (70%:30%, 80%:20%, 90%:10%) menghasilkan tingkat akurasi tertinggi yaitu 89,9% dengan pembagian 90% data training dan 10% data testing.

Abstract

Gojek is an online transportation service that is widely used in Indonesia. It is important for companies to understand how people perceive the quality of the services and products they provide. However, it is difficult to monitor the number of people's opinions to be processed manually. The heading of this research is to classify reviews on the Gojek application and to analyze word associations from the classification results to find out topics that are widely discussed using data from the Google Play page. In this study, several steps of sentiment analysis were carried out, including collecting data, preprocessing, determining sentiment scores, labeling sentiment classes, and classifying data data using the Naïve Bayes Classifier method and carrying out text associations. The Naïve Bayes Classifier method is a simple classification method but produces a high level of accuracy. The research results from data collected on January 1-31 2023 with a total of 4,198 reviews tend to have positive sentiment. The research used the Naïve Bayes Classifier method with three ratios of spliting training and testing data (70%:30%, 80%:20%, 90%:10%) resulting in the highest level of accuracy, namely 89.9% with a 90% division of training data and 10% testing data.

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Published

2023-12-11

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