PENERAPAN PARTICLE SWARM OPTIMIZATION TERHADAP SUPPORT VECTOR MACHINE PADA REVIEW PENGGUNA TRANSPORTASI UDARA

APPLICATION OF PARTICLE SWARM OPTIMIZATION ON SUPPORT VECTOR MACHINE IN REVIEW USER AIR TRANSPORTATION

  • Retno Sari Teknik Informatika STMIK Nusa Mandiri
  • Ratih Yulia Hayuningtyas STMIK Nusa Mandiri
Keywords: Particle Swarm Optimization, Review, Support Vector Machine

Abstract

Air transportation is currently one of the alternative choice in travel by general public. To choose air transportation in accordance with the choice, the buyer can see a review of air transportation. Reviews obtained of text information from varios sources. Sometimes reviews about air transportation make it difficult for buyers to draw conclusions about air transportation information, so we need a method to determine the accuracy of an information. In this study air transportation review uses data of 100 reviews which are used as a dataset and then classified into 50 positive reviews and 50 negative reviews. The dataset will be tested with preprocessing steps and methods. The purpose of this research is the application of Particle Swarm Optimization to Support Vector Machine can increase the value of accuracy. This test resulted in an accuracy rate of 61,03% with AUC 0,953 with Support Vector Machine algorithm, while an accuracy of 71,00% with AUC 0,976 with the Support Vector Machine algorithm optimized with Particle Swarm Optimization. From the test results above, it can be concluded that the research using Support vector Machine algorithm which is optimized with Particle Swarm Optimization has an accuracy level of 9.97%.

References

Brody, S., & Elhadah, N. (2010). An Unsupervised Aspect-Sentiment Model for Online Reviews_Slide. Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the ACL, (June), 804–812. Retrieved from http://www.aclweb.org/anthology/N10-1122

Drajana, I. C. R. (2017). METODE SUPPORT VECTOR MACHINE DAN FORWARD SELECTION PREDIKSI PEMBAYARAN PEMBELIAN BAHAN BAKU. ILKOM Journal Ilmiah, 9, 116–123.

Ling, J., N. Kencana, I. P. E., & Oka, T. B. (2014). Analisis Sentimen Menggunakan Metode Naïve Bayes Classifier Dengan Seleksi Fitur Chi Square. E-Jurnal Matematika, 3(3), 92. https://doi.org/10.24843/mtk.2014.v03.i03.p070

Monarizqa, N., Nugroho, L. E., & Hantono, B. S. (2014). Penerapan Analisis Sentimen Pada Twitter Berbahasa Indonesia Sebagai Pemberi Rating. Jurnal Penelitian Teknik Elektro Dan Teknologi Informasi, 1, 151–155.

Muhamad, H., Prasojo, C. A., Sugianto, N. A., Surtiningsih, L., Cholissodin, I., Ilmu, F., … Optimization, P. S. (2017). OPTIMASI NAÏVE BAYES CLASSIFIER DENGAN MENGGUNAKAN PARTICLE. Jurnal Teknologi Informasi Dan Ilmu Komputer (JTIIK), 4(3), 180–184.

Parapat, I. M., Furqon, M. T., & Sutrisno. (2018). Penerapan Metode Support Vector Machine ( SVM ) Pada Klasifikasi Penyimpangan Tumbuh Kembang Anak. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(10), 3163–3169.

Pravina, A. M., Cholissodin, I., & Adikara, P. P. (2019). Analisis Sentimen Tentang Opini Maskapai Penerbangan pada Dokumen Twitter Menggunakan Algoritme Support Vector Machine ( SVM ). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya, 3(3), 2789–2797.

Rozi, I., Pramono, S., & Dahlan, E. (2012). Implementasi Opinion Mining (Analisis Sentimen) Untuk Ekstraksi Data Opini Publik Pada Perguruan Tinggi. Jurnal EECCIS, 6(1), 37–43.

Rozi, N. F., Arianto, F., & Hapsari, D. P. (2019). Analisis Sentimen Pada Opini Pengguna Maskapai Penerbangan Sentiment Analysis on Passenger Opinions At Airlines Company. Jurnal Teknologi Informasi Dan Ilmu Komputer (JTIIK), 6(3), 321–326. https://doi.org/10.25126/jtiik.201961337

Sari, R., & Hayuningtyas, R. Y. (2019). Penerapan Particle Swarm Optimization Terhadap Support Vector Machine Pada Review Pengguna Transportasi Udara. Laporan Akhir Penelitian Mandiri STMIK Nusa Mandiri Jakarta. Jakarta.

Xue, B., Zhang, M., Member, S., & Browne, W. N. (2012). Particle Swarm Optimization for Feature Selection in Classification : A Multi-Objective Approach. Ieee Transactions on Cybernetics, 43(6), 1–16.

Published
2020-02-01
How to Cite
Sari, R., & Hayuningtyas, R. (2020). PENERAPAN PARTICLE SWARM OPTIMIZATION TERHADAP SUPPORT VECTOR MACHINE PADA REVIEW PENGGUNA TRANSPORTASI UDARA. JITK (Jurnal Ilmu Pengetahuan Dan Teknologi Komputer), 5(2), 165-170. https://doi.org/10.33480/jitk.v5i2.1080
Article Metrics

Abstract viewed = 41 times
PDF downloaded = 35 times