Retno Sari
Teknik Informatika STMIK Nusa Mandiri

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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) Vol 5 No 2 (2020): JITK Issue February 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1047.664 KB) | DOI: 10.33480/jitk.v5i2.1080

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%.
ANALISIS SENTIMEN OPINI PUBLIK BAHASA INDONESIA TERHADAP WISATA TMII MENGGUNAKAN NAÏVE BAYES DAN PSO Ratih Yulia Hayuningtyas; Retno Sari
Jurnal Techno Nusa Mandiri Vol 16 No 1 (2019): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Ma
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (841.918 KB) | DOI: 10.33480/techno.v16i1.115

Abstract

Sentiment analysis is a text analysis to identify an opinion. Public opinion or reviews are important for visitors who will travel to tourist because of the reviews will produce information about the destination. One of the tourist attractions in Indonesia that Taman Mini Indonesia Indah one of the tourist attractions that has extraordinary. Reviews about Taman Mini Indonesia Indah make it difficult for visitors to draw conclusions about information about Taman Mini Indonesia Indah. Therefore a classification method in study with Naïve Bayes and PSO methods. In study using data as many 50 positive reviews and 50 negative reviews where the results of accuracy obtained using the Naïve Bayes method of 70% while the accuracy of using Naïve Bayes and PSO is 94,02%.