Mining Customers Opinion on Services and Applications of Mobile Payment Companies in Indonesia Using Sentiment Analysis Approach

被引:0
作者
Prabaningtyas, Nadhila Idzni [1 ]
Suijandari, Isti [1 ]
Laoh, Enrico [1 ]
机构
[1] Univ Indonesia, Fac Engn, Dept Ind Engn, Depok, Indonesia
来源
2019 16TH INTERNATIONAL CONFERENCE ON SERVICE SYSTEMS AND SERVICE MANAGEMENT (ICSSSM2019) | 2019年
关键词
Text Mining; Sentiment Analysis; N-Grams; Mobile Payment; Support Vector Machine (SVM);
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The development of technology and digital has also increased the ease of accessing the internet. One aspect of daily life that are affected by the adoption of technology and the internet is the field of payment transactions. Payment transactions are inseparable from everyday life. At this time with the development of technology, payment transactions can be done with the more practical, easy, safe and convenient. The technology is called Financial Technology. Mobile payment is a service that is part of financial technology. The aspects contained in the mobile payment are top up, transfers, cash withdrawals, online payment, and offline payments. Classifications of reviews from Twitter are classified using Support Vector Machine. The results of this study are Go-Pay and OVO must pay attention to every aspect and improve every aspect, of course, to increase customer satisfaction. The accuracy level of the classification model produced for bigram is 92% (Go-Pay) and 93% (OVO). It also shows that sentiment analysis using bigram can improve accuracy level.
引用
收藏
页数:5
相关论文
共 19 条
  • [1] Aggarwal R., 2007, INT J COMPUTER SCI M, V6, P149
  • [2] [Anonymous], 2018, REP
  • [3] [Anonymous], 2012, SENTIMENT ANAL OPINI
  • [4] [Anonymous], 2003, P 12 INT C WORLD WID, DOI DOI 10.1145/775152.775226
  • [5] [Anonymous], 2017, REP
  • [6] Text-mining Techniques and Tools for Systematic Literature Reviews: A Systematic Literature Review
    Feng, Luyi
    Chiam, Yin Kia
    Lo, Sin Kuang
    [J]. 2017 24TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2017), 2017, : 41 - 50
  • [7] Goyal S., 2016, INT J ADV RES IDEAS, V2
  • [8] Hofmann Markus., 2016, Text Mining and Visualization: Case Studies Using Open-Source Tools
  • [9] Hoofnagle C. J., 2012, SSRN ELECT J
  • [10] Joachims T, 1998, P 10 EUR C MACH LEAR, P137, DOI DOI 10.1007/BFB0026683