Klasifikasi Pengguna QRIS Berdasarkan Frekuensi Penggunaan Menggunakan Multinomial Logistic Regression

Dani Daniel Gimon
Rivaldo Otniel Moreno Sabami
Khrisna Andhika Bagaskara
Owen Tomas Kayadu
Theos Elasa Numberi

Sci-Tech Journal
Vol. 4 No. 2 (2025): Sci-Tech Journal

This study focuses on developing a classification model of Quick Response Code Indonesian Standard (QRIS) users based on usage frequency by applying the Multinomial Logistic Regression (MLR) method. Data were obtained through a survey of QRIS users, with 265 respondents comprising the research sample. An analysis was conducted to identify demographic and behavioral factors that significantly influence QRIS usage frequency. The results demonstrate the effectiveness of the MLR model in classifying QRIS users into different usage frequency categories with a high level of accuracy. Variables such as age, gender, and transaction time were found to significantly influence QRIS usage frequency. This research has theoretical and practical implications for stakeholders, including QRIS service providers, who can use the findings to design more effective marketing strategies and personalize services to suit the needs of different user segments.