TY - JOUR
T1 - Fintech Lending in Indonesia
T2 - A Sentiment Analysis, Topic Modelling, and Social Network Analysis using Twitter Data
AU - Utami, Sri Handika
AU - Purnama, Anton Ade
AU - Hidayanto, Achmad Nizar
N1 - Publisher Copyright:
© Roman Science Publications.
PY - 2022/6
Y1 - 2022/6
N2 - Digitalization in financing industries, has brought us into Financial Technology (Fintech). Fintech proved to be much more accessible to people with low financial literacy. Fintech Lending is one kind of business in fintech. Also known as Pinjol, Fintech Lending become one of the trending topics on Indonesian Twitter, which unfortunately is more about illegal Pinjol, which brings so many insecurities for government, financial regulations, and pinjol company itself. With this research, the sentiment and central character were analyzed. Using several algorithms for data model creation, Naïve Bayes is the most performing one, giving us the fact that negative sentiment still takes the lead on the earlier day of observation, but it decreased over time. We also discovered the most influential character on the issue, to help interested parties to deal with correction, confirmation, and endorsement to support the regulation and survival of the business. Using the pic model, the study concludes that despite its negative sentiment, pinjol still has a good opportunity to grow with the support of government, regulator, and law enforcement team. The policy, regulation, and government resources had to comply with the development speed of pinjol.
AB - Digitalization in financing industries, has brought us into Financial Technology (Fintech). Fintech proved to be much more accessible to people with low financial literacy. Fintech Lending is one kind of business in fintech. Also known as Pinjol, Fintech Lending become one of the trending topics on Indonesian Twitter, which unfortunately is more about illegal Pinjol, which brings so many insecurities for government, financial regulations, and pinjol company itself. With this research, the sentiment and central character were analyzed. Using several algorithms for data model creation, Naïve Bayes is the most performing one, giving us the fact that negative sentiment still takes the lead on the earlier day of observation, but it decreased over time. We also discovered the most influential character on the issue, to help interested parties to deal with correction, confirmation, and endorsement to support the regulation and survival of the business. Using the pic model, the study concludes that despite its negative sentiment, pinjol still has a good opportunity to grow with the support of government, regulator, and law enforcement team. The policy, regulation, and government resources had to comply with the development speed of pinjol.
KW - Fintech Lending
KW - Indonesian Twitter
KW - Pinjol
KW - sentiment analysis
KW - social network analysis
KW - topic model
UR - http://www.scopus.com/inward/record.url?scp=85139509218&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85139509218
SN - 2633-4828
VL - 4
SP - 50
EP - 56
JO - International Journal of Applied Engineering and Technology (London)
JF - International Journal of Applied Engineering and Technology (London)
IS - 1
ER -