CircleCube

Dataset

Indonesian Digital Banking App Reviews: Aladin, Jago, and BYOND by BSI

September 2, 2026Open Access

This dataset contains user reviews collected from three digital banking applications available on the Google Play Store in Indonesia:

  • Bank Jago
  • Bank Aladin
  • BYOND by BSI (Bank Syariah Indonesia)

The reviews were collected automatically using the google-play-scraper Python library, with the Newest Reviews sorting method. The dataset is intended to support research and practical analysis of user experiences, sentiment, service quality, and recurring issues in Indonesian digital banking applications.

Dataset Objectives

This dataset can be used for:

  • Sentiment analysis of digital banking users
  • User experience and service quality evaluation
  • Comparison of customer perceptions across banking applications
  • Detection of rating–review mismatches
  • Identification of recurring complaints and application issues
  • Natural Language Processing (NLP) and text classification research
  • Topic modeling and customer feedback analysis

Data Sources

The data was collected from the respective applications’ pages on the Google Play Store using Python and the google-play-scraper library.

Applications Covered

ApplicationApprox. Reviews
Bank Jago68,719
Bank Aladin30,243
BYOND by BSI57,005
Total155,000+

Data Fields

The review files contain information such as:

  • reviewId — Unique identifier for each review
  • userName — Display name of the reviewer
  • userImage — URL of the reviewer’s profile image
  • content — Review text
  • score — User rating from 1 to 5
  • thumbsUpCount — Number of likes received by the review
  • reviewCreatedVersion — Application version when the review was submitted
  • at — Review timestamp
  • replyContent — Developer response to the review, when available
  • repliedAt — Timestamp of the developer response
  • appVersion — Application version associated with the review

Potential Research Applications

The dataset is particularly suitable for studies involving Sentiment Analysis, Natural Language Processing, Text Classification, Topic Modeling, Aspect-Based Sentiment Analysis (ABSA), and User Experience Analysis.

For example, researchers can investigate whether low ratings are primarily associated with issues such as login problems, face verification failures, QRIS transactions, maintenance, customer service, or other banking features. Researchers can also compare user sentiment across the three applications and examine how customer complaints change across application versions.

Data Period

The reviews cover the period represented in the collected data, with the available records extending from 2022 to 2026. The dataset represents reviews collected during the scraping process and may not represent every review available on the Google Play Store.