Naïve Bayes Optimization by Implementing Genetic Algorithm in Sentiment Analysis of BCA Mobile Reviews

Muhammad Enricco Rizqy; Ahmad Faqih; Gifthera Dwilestari

doi:10.59934/jaiea.v4i2.750

Authors

Muhammad Enricco Rizqy STMIK IKMI Cirebon
Ahmad Faqih STMIK IKMI Cirebon
Gifthera Dwilestari STMIK IKMI Cirebon

DOI:

https://doi.org/10.59934/jaiea.v4i2.750

Keywords:

Genetic algorithm, Naive Bayes, Sentimen Analysis, Bank Application, Optimization

Abstract

The development of the digital era has encouraged the adoption of mobile banking applications that facilitate banking transactions, including the BCA Mobile application which is simple but still adheres to a slightly outdated, user-friendly appearance but to provide the best service, it is necessary to evaluate the various problems that arise through review analysis. This study aims to conduct sentiment analysis of BCA Mobile application reviews taken from the Google Play Store, with data totaling 1,200 reviews scraping results using Google Collaboratory python programming language, to categorize negative and positive reviews used manual labeling for more accurate results, the Naïve Bayes approach is used in classifying positive and negative category reviews due to the ability of this algorithm to handle text data. However, the weakness of Naïve Bayes which is sensitive to irrelevant features can cause a decrease in accuracy. This research implements Genetic algorithm to improve the performance of Naïve Bayes. The results showed that the application of Genetic algorithm successfully increased the accuracy, precision of Naïve Bayes classification 95%, precision 92% to accuracy 98%, precision 99%, which proved the effectiveness of Genetic algorithm in optimizing the model and improving the quality of sentiment analysis.

Downloads

Download data is not yet available.

References

V. Tundjungsari and S. Wijaya, “Sentimen Analisis Pada Aplikasi E-Branch BCA Menggunakan Metode Naive Bayes,” IKRA-ITH Teknologi Jurnal Sains dan Teknologi, vol. 8, no. 1, pp. 78–87, Mar. 2024.

D. Wahyu Bhatara and R. Randy Suryono, “Analisis Sentimen Aplikasi BCA Mobile Menggunakan Algoritma Naïve Bayes Dan Support Vector Machine,” https://jurnal.stkippgritulungagung.ac.id/index.php/jipi/article/view/5536, vol. 9, no. 4, pp. 1907–1917, 2024, doi: 10.29100/jipi.v9i4.5536.

M. Rizky Pratama, Y. R. Ramadhan, and M. A. Komara, “Analisis Sentimen BRImo dan BCA Mobile Menggunakan Support Vector Machine dan Lexicon Based,” vol. 12, 2023.

A. Hendra and F. Fitriyani, “Analisis Sentimen Review Halodoc Menggunakan Nai ̈ve Bayes Classifier,” JISKA (Jurnal Informatika Sunan Kalijaga), vol. 6, no. 2, pp. 78–89, May 2021, doi: 10.14421/jiska.2021.6.2.78-89.

A. Rahman, E. Utami, and S. Sudarmawan, “Sentimen Analisis Terhadap Aplikasi pada Google Playstore Menggunakan Algoritma Naïve Bayes dan Algoritma Genetika,” Jurnal Komtika (Komputasi dan Informatika), vol. 5, no. 1, pp. 60–71, Jul. 2021, doi: 10.31603/komtika.v5i1.5188.

S. F. Tahir and C. A. Sugianto, “Optimasi Naive Bayes Menggunakan Algoritma Genetika Pada Klasifikasi Komentar Cyberbullying Pada Media Sosial X,” Jurnal Informatika dan Teknik Elektro Terapan, vol. 12, no. 3, pp. 3350–3356, Aug. 2024, doi: 10.23960/jitet.v12i3.4834.

W. Astuti, R. Kurniawan, and Y. A. Wijaya, “Jurnal Informatika dan Rekayasa Perangkat Lunak Analisis Data Sentimen Ulasan Aplikasi Dana di Google Play Store Menggunakan Algoritma Naïve Bayes,” vol. 6, no. 1, pp. 158–163, 2024.

W. Wahyudi, R. Kurniawan, and A. Y. Wijaya, “Analisis Sentimen Pengguna Terhadap Aplikasi Blu Bca Di Playstore Mengunakan Algoritma Naïve Bayes,” vol. 8, no. 3, pp. 2511–2517, May 2024.

J. Teknika, M. K. Rifa, M. H. Totohendarto, and M. R. Muttaqin, “Analisis Sentimen Penguna E-Wallet Dana Dan Gopay Pada Twitter Menggunakan Metode Support Vector Machine (SVM),” IJCCS, vol. 17, no. 2, pp. 323–332, Aug. 2023.

A. Suryana, A. I. Purnamasari, and I. Ali, “Mengoptimalkan Kepuasan Pengguna: Analisis Sentimen Review Aplikasi Grab Di Indonesia,” Jl.Perjuangan No.10 B Majasem, Kec.Kesambi, Kota Cirebon Jawa Barat 45135, Indonesia, Jun. 2024. Accessed: May 29, 2024. [Online]. Available: https://ejournal.itn.ac.id/index.php/jati/article/view/9688/5524

S. M. Salsabila, A. Alim Murtopo, and N. Fadhilah, “Analisis Sentimen Pelanggan Tokopedia Menggunakan Metode Naïve Bayes Classifier,” Jurnal Minfo Polgan, vol. 11, no. 2, pp. 30–35, Aug. 2022, doi: 10.33395/jmp.v11i2.11640.

M. K. Khoirul Insan, U. Hayati, and O. Nurdiawan, “Analisis Sentimen Aplikasi Brimo Pada Ulasan Pengguna Di Google Play Menggunakan Algoritma Naive Bayes,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 7, no. 1, pp. 478–483, Mar. 2023, doi: 10.36040/jati.v7i1.6373.

N. Agustina, D. H. Citra, W. Purnama, C. Nisa, and A. R. Kurnia, “Implementasi Algoritma Naive Bayes untuk Analisis Sentimen Ulasan Shopee pada Google Play Store,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 2, no. 1, pp. 47–54, Apr. 2022, doi: 10.57152/malcom.v2i1.195.

K. Anwar, “Analisa sentimen Pengguna Instagram Di Indonesia Pada Review Smartphone Menggunakan Naive Bayes,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 2, no. 4, pp. 148–155, Feb. 2022, doi: 10.30865/klik.v2i4.315.

A. F. Watratan, A. P. B, and D. Moeis, “Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia,” Journal of Applied Computer Science and Technology, vol. 1, no. 1, pp. 7–14, Jul. 2020, doi: 10.52158/jacost.v1i1.9.