Strategic Expansion of Digital Payments in Papua and West Papua: Individual Character Analysis Using Random Over and Under Sampling CART
DOI:
https://doi.org/10.34123/icdsos.v2025i1.651Keywords:
Classification and Regression Trees (CART), Digital payments, e-banking, ResamplingAbstract
This study examines the characteristics and influencing factors of digital payment usage among individuals in Papua and West Papua. Understanding these characteristics enables stakeholders to design effective strategies for promotion, socialization, and education to support the expansion of digital payment adoption. The analysis uses data from the March 2023 National Socio-Economic Survey conducted by BPS, involving 52,081 respondents aged 17 years and older. A Classification and Regression Trees (CART) approach was applied with random oversampling and undersampling techniques to handle data imbalance. The results reveal that business fields, types of residential areas, and education levels are key determinants of digital payment usage. Three primary user profiles were identified: (1) individuals aged 17+ working outside the agricultural sector with at least a high school education; (2) individuals aged 17+ working outside agriculture, with junior high school education or below, residing in urban areas; and (3) individuals aged 17+ working in agriculture or unemployed, living in urban areas, and having completed high school or higher. These findings suggest that stakeholders should tailor promotional strategies and educational programs based on individual characteristics to effectively increase digital payment adoption in Papua and West Papua.