Author
Putri Yusra Haliza(1
), Angga Tamara(2), Christoffel Mario(3), Yizhar Saputra Hondro(4), Linda Natasya Siahaan(5), Syairal Fahmy Dalimunthe(6),
(1) Universitas Negeri Medan,
(2) Universitas Negeri Medan,
(3) Universitas Negeri Medan,
(4) Universitas Negeri Medan,
(5) ,
(6) ,
Corresponding Author
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Available online: 2025-03-24 | Published : 2025-03-24
Copyright (c) 2025 Putri Yusra Haliza, Angga Tamara, Christoffel Mario
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Abstract
This study aims to analyze the factors influencing car purchase decisions using binary logistic regression. Data were obtained from 1,000 respondents with independent variables including age, marital status, gender, car ownership, and income. The analysis results show that marital status, gender, and income significantly influence purchase decisions. Married respondents tend to have a lower likelihood of purchasing a car compared to single respondents, while females have a smaller tendency compared to males. On the other hand, higher income significantly increases the probability of car purchase. The constructed binary logistic regression model has a prediction accuracy of 93.8%, demonstrating its reliability in classifying purchase decisions. This study provides valuable insights for the automotive industry in designing effective and targeted marketing strategies. Additionally, further exploration of other factors such as brand preferences, geographic location, and psychological factors is recommended to enrich the understanding of automotive market behavior.
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References
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