PayPal Usage in Indonesia with k-Nearest Neighbor Algorithm

The development of information and digital technology has had a significant impact on the financial sector. In Indonesia, digital payment technologies such as PayPal, Gopay, Shopeepay, OVO, and DANA have become an integral part of the modern payment system. Since 2005, the implementation of the national electronic clearing system, RTGS, and ATMs have facilitated various payment methods. Sentiment analysis of PayPal provides in-depth insights into user experience, enabling improved service quality and more effective marketing strategies. Sentiment data helps PayPal in making better business decisions and managing brand reputation. This study compares PayPal usage in Indonesia from a user perspective, with a focus on sentiment analysis, to identify factors that influence the acceptance of this platform in various markets. This study aims to provide valuable insights for the development and updating of PayPal service policies.

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Publication Details

Journal
UNP Journal of Statistics and Data Science
Published
2025-08-30
DOI
https://doi.org/10.24036/ujsds/vol3-iss3/405
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

PayPal Usage in Indonesia with k-Nearest Neighbor Algorithm

Dodi Vionanda, Amannia zeze, Muhammad Ravi Azzaki
UNP Journal of Statistics and Data Science
Data Mining and Machine Learning Applications
article

PayPal Usage in Indonesia with k-Nearest Neighbor Algorithm

Dodi Vionanda, Amannia zeze, Muhammad Ravi Azzaki
article en

Abstract

The development of information and digital technology has had a significant impact on the financial sector. In Indonesia, digital payment technologies such as PayPal, Gopay, Shopeepay, OVO, and DANA have become an integral part of the modern payment system. Since 2005, the implementation of the national electronic clearing system, RTGS, and ATMs have facilitated various payment methods. Sentiment analysis of PayPal provides in-depth insights into user experience, enabling improved service quality and more effective marketing strategies. Sentiment data helps PayPal in making better business decisions and managing brand reputation. This study compares PayPal usage in Indonesia from a user perspective, with a focus on sentiment analysis, to identify factors that influence the acceptance of this platform in various markets. This study aims to provide valuable insights for the development and updating of PayPal service policies.

UNP Journal of Statistics and Data ScienceVol. 3(3)
State University of Padang (ID)
Openalex Percentile: Top 64%
Data Mining and Machine Learning Applications
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