Sentiment Analysis Review Flip App Users on Google Play Using Naïve Bayes Algorithm and Support Vector Machine with Smote Technique

Sentiment Analysis Review Flip App Users on Google Play Using Naïve Bayes Algorithm and Support Vector Machine with Smote Technique

• By Y KUNTORO, ANTONIUS;
• Jurnal Internasional
• 133
• 253-260

Abstract. The development of e-wallet is now increasingly sophisticated, can provide convenience to its customers in
transacting anytime and anywhere just by using a smartphone. From some e-wallet products researchers took a case study
that is FLIP products that are currently going viral, especially in Jakarta. Customers who are dissatisfied with a
company’s services or products will typically write their complaints on social media or reviews on Google play.
However, monitoring and organizing public opinion is also not easy. Therefore, a special method or technique is required
that is able to categorize the reviews automatically, whether including positive or negative. The algorithms used in this
study were Naïve Bayes and Support Vector Machine with smote techniques. Naïve Bayes had an accuracy score of
64.55% with an AUC of 0.502 while Naive Bayes with smote technique gained 69.78% accuracy with an AUC of 0.506.
While SVM has an accuracy value of 65.00% with AUC 0.786, while SVM with smote technique has an accuracy value
of 73.48% and AUC 0.836. The best optimization application in this model is SVM with smote technique can provide
solutions to classification problems in the case of sentiment analysis of FLIP app user reviews.

• Katakunci Sentiment Analysis Review Flip App Users on Google Play Using Naïve Bayes Algorithm and Support Vector Machine with Smote Technique
• URL http://https://pubs.aip.org/aip/acp/article-abstract/2714/1/020036/2889736/Sentiment-analysis-review-flip-app-users-on-Google?redirectedFrom=fulltext
• Penerbit ICAISD 2021,

REFERENSI

REFERENCES
1. Lu Y Yang S Chau P Y K and Cao Y, 2011 Dynamics between the trust transfer process and intention to use
mobile payment services: A cross-environment perspective Inf. Manag. 48, 8 p. 393–403
2. Buntoro G A, 2017 Analisis Sentimen Calon Gubernur DKI Jakarta 2017 Di Twitter INTEGER J. Inf. Technol.
1, 1 p. 32–41.
3. Dhande L L and Patnaik G K, 2014 Analyzing Sentiment of Movie Review Data using Naive Bayes Neural
Classifier Int. J. Emerg. Trends Technol. Comput. Sci. 3, 4 p. 313–320.
4. Nurhuda F Widya Sihwi S and Doewes A, 2016 Analisis Sentimen Masyarakat terhadap Calon Presiden
Indonesia 2014 berdasarkan Opini dari Twitter Menggunakan Metode Naive Bayes Classifier J. Teknol. Inf.
ITSmart 2, 2 p. 35
5. Aditia Rakhmat Sentiaji A M B Sarjana P S Statistika D Matematika F Ilmu D A N and Alam P, 2014 Analisis
Sentimen Terhadap Acara Televisi Berdasarkan Opini Publik J. Ilm. Komput. dan Inform.
6. Anjani D, 2015 Analisis Kemiripan Dokumen Tugas Akhir Untuk Penilaian Originalitas Bandung 30, 3 p.
243–250.
7. Hermanto Kuntoro A Y Asra T Pratama E B Effendi L and Ocanitra R, 2020 Gojek and Grab User Sentiment
Analysis on Google Play Using Naive Bayes Algorithm and Support Vector Machine Based Smote Technique
J. Phys. Conf. Ser. 1641, 1.
8. Saputra N Adji T B and Permanasari A E, 2015 Analisis Sentimen Data Presiden Jokowi dengan Preprocessing
Normalisasi dan Stemming Menggunakan Metode Naive Bayes dan SVM J. Din. Inform. 5, November p.
12.
9. Hermanto and Noviriandini A, 2021 ANALISA SENTIMEN TERHADAP BELAJAR ONLINE PADA
MASA COVID-19 MENGGUNAKAN ALGORITMA SUPPORT VECTOR 5, 1 p. 129–136.
10. Slamet C Atmadja A R Maylawati D S Lestari R S Darmalaksana W and Ramdhani M A, 2018 Automated
Text Summarization for Indonesian Article Using Vector Space Model IOP Conf. Ser. Mater. Sci. Eng. 288,
1.
020036-7
11. Puspitasari A M Ratnawati D E and Widodo A W, 2018 Klasifikasi Penyakit Gigi Dan Mulut Menggunakan
Metode Support Vector Machine J. Pengemb. Teknol. Inf. dan Ilmu Komput. 2, 2 p. 802–810.
12. Santoso V I Virginia G and Lukito Y, 2017 Penerapan Sentiment Analysis Pada Hasil Evaluasi Dosen Dengan
Metode Support Vector Machine J. Transform. 14, 2 p. 72.
13. Anggraini R A Widagdo G Budi A S and Qomaruddin M, 2019 Penerapan Data Mining Classification untuk
Data Blogger Menggunakan Metode Na¨ıve Bayes J. Sist. dan Teknol. Inf. 7, 1 p. 47.