Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Madani: Multidisciplinary Scientific Journal Tashdiq: Jurnal Kajian Agama dan Dakwah
Tamara, Angga
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Madani: Multidisciplinary Scientific Journal

 1 
Analisis Faktor-faktor yang Mempengaruhi Keputusan Pembelian Mobil Menggunakan Regresi Logistik Biner Haliza, Putri Yusra; Tamara, Angga; Mario, Christoffel; Hondro, Yizhar Saputra; Siahaan, Linda Natasya; Dalimunthe, Syairal Fahmy
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 2 (2025): March
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15077946

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.
Co-Authors Aqil, Muhammad Fachri Br Barus, Jesika Casadae Wanda Haliza, Putri Yusra Harahap, Adi Gunawan Hondro, Yizhar Saputra Hutapea, Brian Kairani, Nerli Lubis, Hafiz Khalik Lubis, M. Shadri Ismaun Manullang, Sudianto Mario, Christoffel Nadya, Fauza Nurmayani Pulungan, Zakiy Maulana Siahaan, Linda Natasya Silaban, Dewi Fortuna Sinaga, Marlina Setia Syairal Fahmy Dalimunthe Triono, Wira