Sentiment Analysis Of Public Comments On Licensing Services Seeks To Use The Naive Bayes Algorithm With Genetic Selection Algorithm

Abdulatif Patue; Guruh Fajar Sidik; Affandy Affandy; Abdul Rahman Ismail

doi:10.32520/stmsi.v13i1.3550

Sentiment Analysis Of Public Comments On Licensing Services Seeks To Use The Naive Bayes Algorithm With Genetic Selection Algorithm

Abdulatif Patue, Guruh Fajar Sidik, Affandy Affandy, Abdul Rahman Ismail

Abstract

The Investment and One-Stop Integrated Service Office is the Licensing Service service to support an area in terms of business potential and investment value. Presenting MSME Business Actors and Young Entrepreneurs. As time goes by, Licensing Services in the Region, especially PTSP, must know what are the constraints and problems faced by business actors in terms of business services and products issued by the Service. Naïve Bayes is the most common algorithm that we encounter in several libraries. Therefore, this research will discuss the level of accuracy of this algorithm. Then additional selection of Genetic Algorithm features was carried out to increase the accuracy of the Naïve Bayes method. The Naive Bayes Algorithm method with Genetic Algorithm selection is superior compared to only using the Naive Bayes method. This is proven by the acquisition of 83.17% accuracy, 86.38% Precision, and 83.05% recall

Full Text:

PDF

References

R. A. Cahya, D. Adimanggala, and A. A. Supianto, “Deep Feature Weighting Based on Genetic Algorithm and Naïve Bayes for Twitter Sentiment Analysis,” in 2019 International Conference on Sustainable Information Engineering and Technology (SIET), Lombok, Indonesia: IEEE, Sep. 2019, pp. 326–331. doi: 10.1109/SIET48054.2019.8986107.

A. Radaideh, F. Dweiri, and M. Obaidat, “A Novel Approach to Predict the Real Time Sentimental Analysis by Naive Bayes & RNN Algorithm during the COVID Pandemic in UAE,” in 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI), Sharjah, United Arab Emirates: IEEE, Nov. 2020, pp. 1–5. doi: 10.1109/CCCI49893.2020.9256587.

F.-J. Yang, “An Implementation of Naive Bayes Classifier,” in 2018 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA: IEEE, Dec. 2018, pp. 301–306. doi: 10.1109/CSCI46756.2018.00065.

Y. K. Saheed, M. A. Hambali, M. O. Arowolo, and Y. A. Olasupo, “Application of GA Feature Selection on Naive Bayes, Random Forest and SVM for Credit Card Fraud Detection,” in 2020 International Conference on Decision Aid Sciences and Application (DASA), Sakheer, Bahrain: IEEE, Nov. 2020, pp. 1091–1097. doi: 10.1109/DASA51403.2020.9317228.

A. M. Rahat, A. Kahir, and A. K. M. Masum, “Comparison of Naive Bayes and SVM Algorithm based on Sentiment Analysis Using Review Dataset,” in 2019 8th International Conference System Modeling and Advancement in Research Trends (SMART), Moradabad, India: IEEE, Nov. 2019, pp. 266–270. doi: 10.1109/SMART46866.2019.9117512.

J. Li and Y. Liang, “Refining Word Embeddings Based on Improved Genetic Algorithm for Sentiment Analysis,” in 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Chongqing, China: IEEE, Dec. 2020, pp. 213–216. doi: 10.1109/ITAIC49862.2020.9339058.

N. Morozs, T. Clarke, and D. Grace, “Heuristically Accelerated Reinforcement Learning for Dynamic Secondary Spectrum Sharing,” IEEE Access, vol. 3, pp. 2771–2783, 2015, doi: 10.1109/ACCESS.2015.2507158.

A. R. Ismail, I. Labolo, and Y. Handayani, “Implementation of JSON Parsing in Agricultural Productive Learning Applications,” SISTEMASI, vol. 12, no. 1, p. 269, Jan. 2023, doi: 10.32520/stmsi.v12i1.2673.

M. Wongkar and A. Angdresey, “Sentiment Analysis Using Naive Bayes Algorithm Of The Data Crawler: Twitter,” in 2019 Fourth International Conference on Informatics and Computing (ICIC), Semarang, Indonesia: IEEE, Oct. 2019, pp. 1–5. doi: 10.1109/ICIC47613.2019.8985884.

P. P. Surya and B. Subbulakshmi, “Sentimental Analysis using Naive Bayes Classifier,” in 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN), Vellore, India: IEEE, Mar. 2019, pp. 1–5. doi: 10.1109/ViTECoN.2019.8899618.

S. Ernawati, E. R. Yulia, Frieyadie, and Samudi, “Implementation of The Naïve Bayes Algorithm with Feature Selection using Genetic Algorithm for Sentiment Review Analysis of Fashion Online Companies,” in 2018 6th International Conference on Cyber and IT Service Management (CITSM), Parapat, Indonesia: IEEE, Aug. 2018, pp. 1–5. doi: 10.1109/CITSM.2018.8674286.

W. M. P.D. and Haryoko, “Optimization Of Parameter Support Vector Machine (SVM) using Genetic Algorithm to Review Go-Jek’s Services,” in 2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), Yogyakarta, Indonesia: IEEE, Nov. 2019, pp. 301–304. doi: 10.1109/ICITISEE48480.2019.9003894.

B. P. Jocom, N. Hidayat, and P. P. Adikara, “Penerapan Genetic Algorithm Untuk Optimasi Peningkatan Laba Persediaan Produksi Pakaian”.

A. R. Ismail, A. Zainul Fanani, G. F. Shidik, and Muljono, “Implementation Of Naive Bayes Algorithm With Particle Swarm Optimization In Classification Of Dress Recommendation,” in 2020 International Seminar on Application for Technology of Information and Communication (iSemantic), Semarang, Indonesia: IEEE, Sep. 2020, pp. 174–178. doi: 10.1109/iSemantic50169.2020.9234293.

F. Harahap, A. Y. N. Harahap, E. Ekadiansyah, R. N. Sari, R. Adawiyah, and C. B. Harahap, “Implementation of Naïve Bayes Classification Method for Predicting Purchase,” in 2018 6th International Conference on Cyber and IT Service Management (CITSM), Parapat, Indonesia: IEEE, Aug. 2018, pp. 1–5. doi: 10.1109/CITSM.2018.8674324.

DOI: https://doi.org/10.32520/stmsi.v13i1.3550

Article Metrics

Abstract view : 68 times
PDF - 20 times

Refbacks

There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Username
Password
Remember me