Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP

Nanda Mediya Sari ; Jasmir Jasmir ; Elvi Yanti
Prosiding Seminar Nasional Ilmu Teknik 📅 2025 Vol 2, No 2 🔗 DOI: 10.61132/prosemnasproit.v2i2.65
Abstract
Sentiment analysis is a technique in Natural Language Processing (NLP) used to identify user opinion tendencies based on textual reviews. This study analyzer user reviews of the Maxim application on the Google Play Store and compares three Machine Learning algoritmhs-Naïve Bayes, Support Vector Machine (SVM), and CatBoost-in classifying sentiment. The research stages include data collection, text preprocessing, feature extraction using TF-IDF and Chi-Square, class balancing using SMOTE, and performance evaluation through Accuracy, Precision, Recall, and F1-Score. ANOVA is used to examine the influence of feature selection on model performance. The results show that each model exhibits different performance level across the tested feature combinations. The CatBoost achieved the highest accuracy of 99,26% and demonstrating the most stable performance. Meanwhile, the Naïve Bayes and SVM models experienced performance decreases experiments, especially after applying SMOTE. These findings indicate that the choise of algorithm, feature extraction method, and class balancing technique significantly affects classification outcomes. Overall, CatBoost is identified as the best-performing model, providing more consistenst classification result in accordance with the characteristics of the user reviews.
Keywords
CatBoost; Naive Bayes; Analisis Sentimen; Support Vector Machine
How to Cite

Nanda Mediya Sari, et al. (2025). Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP. Prosiding Seminar Nasional Ilmu Teknik, 2(2). https://doi.org/10.61132/prosemnasproit.v2i2.65

Nanda Mediya Sari; Jasmir Jasmir; Elvi Yanti, "Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP," Prosiding Seminar Nasional Ilmu Teknik, vol. 2, no. 2, 2025.

Nanda Mediya Sari; Jasmir Jasmir; Elvi Yanti. "Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP." Prosiding Seminar Nasional Ilmu Teknik, vol. 2, no. 2, 2025.

Nanda Mediya Sari; Jasmir Jasmir; Elvi Yanti. "Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP." Prosiding Seminar Nasional Ilmu Teknik 2, no. 2 (2025).

Nanda Mediya Sari, et al. (2025) 'Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP', Prosiding Seminar Nasional Ilmu Teknik, 2(2). doi: 10.61132/prosemnasproit.v2i2.65.

Nanda Mediya Sari; Jasmir Jasmir; Elvi Yanti. Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP. Prosiding Seminar Nasional Ilmu Teknik. 2025;2(2).

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