PayPal Usage in Indonesia with K-Nearest Neighbor Algorithm

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 the implementation of the national electronic clearing system, RTGS, and ATMs in 2005, transactions have become increasinglyconvenient. This study analyzes user sentiment toward PayPal in Indonesia to understand user experience and provide insights for service development, marketing strategies, and brand reputation management. Review data from the PayPal app was collected from Google Plat via web scrapping and processed to yield 597 clean data points. Initial sentiment was categorized into positive, neutral, and negative, wordcloud visualization displayed positive and negative sentiment, while neutral sentiment was analyzed numerically. Automatic labeling was performed using the NLTK library based on rating values, above 3 positive, below 3 negative, and exactly 3 neutral. The results showed 146 positive reviews, 451 negative reviews, and a few neutral reviews. Sentiment classification using the K-Nearest Neighbor (K-NN) method yielded adequate accuracy, indicating that PayPal's acceptance in Indonesia is largely influenced by users' negative experiences. These findings provide a foundation for developing strategies to improve service quality and update PayPal's operational policies in the Indonesian market.