PENERAPAN PARTICLE SWARM OPTIMIZATION TERHADAP SUPPORT VECTOR MACHINE PADA REVIEW PENGGUNA TRANSPORTASI UDARA - Retno Sari; Ratih Yulia Hayuningtyas (JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), 2020)
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%.