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Khrisna Andhika Bagaskara
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Public Health

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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
Publisher : MES Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/stj.v4i3.802

Abstract

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.
Co-Authors Dani Daniel Gimon Owen Tomas Kayadu Rivaldo Otniel Moreno Sabami Theos Elasa Numberi