Public Perception for the use of Digital Wallet in Indonesia using Social Network Analysis

DOI

10.2991/aebmr.k.211226.008How to use a DOI?

Keywords

perception; GoPay; OVO; Naïve Bayes; social network analysis

Abstract

The development of financial technology is currently growing by payment transactions can be done easily using digital wallets, so customers do not need to use cash to make some payments. The competition of fintech service providers in Indonesia is getting more competitive, based on the varied services offered as the company’s strategy to maintain customer satisfaction. The problem arises in how the public perceives the benefits of mobile payment service providers GoPay and OVO as the top digital wallet in the second quarter of 2019. Companies can use social media to see how the company works by public perception because the public uses Twitter to convey messages, comments, and complaints about the services provided by the company. This study aims to analyze the public views of the two companies by combining sentiment analysis using Naïve Bayes to identify positive and negative perceptions and social network analysis to know the interaction between the public. Sentiment analysis using TF-IDF feature selection and Naïve Bayes classification generate GoPay accuracy is 80.42%, and OVO is 82.44%. Positive sentiment towards the use of GoPay and OVO has a higher value. The network on SNA shows that nodes that are not connected to the gojekindonesia and ovo_id node have more positive perceptions, namely perceptions related to promos, cashback and discounts on the use of GoPay and OVO.

Copyright

© 2021 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Desanty Ridzky
AU  - Mohammad Isa Irawan
PY  - 2021
DA  - 2021/12/31
TI  - Public Perception for the use of Digital Wallet in Indonesia using Social Network Analysis
BT  - Proceedings of the 3rd International Conference on Business and Management of Technology (ICONBMT 2021)
PB  - Atlantis Press
SP  - 56
EP  - 63
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.211226.008
DO  - 10.2991/aebmr.k.211226.008
ID  - Ridzky2021
ER  -