Uncovering Hidden Sentiments and Topics in Online Lending Application Reviews with the Valence Aware Dictionary and sEntiment Reasoner (VADER) and Latent Dirichlet Allocation (LDA) Approaches

Fikri Fahru Roji (Universitas Garut)
Windi Ariesti Anggraeni (Universitas Garut)
Riyad Sabilul Muminin (Universitas Garut)
Dendi Ramdani (Universitas Garut)
Yayan Cahyan (Universitas Sebelas Apri)

RISTEC : Research in Information Systems and Technology
Vol. 4 No. 2 (2023): RISTEC : Research in Information Systems and Technology

Online lending (pinjol) has become an important part of the digital transformation of the financial sector, offering people easy access to funds. However, the increasing reliance on user reviews as a decision-making factor raises concerns about their authenticity and credibility. This research aims to analyze the sentiments and topics that appear in the reviews of Akulaku, Kredivo, and EasyCash lending apps on the Google Play Store. Using text mining techniques, VADER sentiment analysis, and LDA topic modeling, this research reveals dominant positive sentiments related to ease of use, service speed, and customer support. However, there were also negative reviews regarding loan application difficulties, technical issues, and bad experiences with billing and payments. This research provides valuable insights into the preferences and concerns of pinjol users, which can serve as a reference for service providers to improve the quality of their products and services.