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All Journal Madani: Multidisciplinary Scientific Journal Socius: Social Sciences Research Journal
Mario, Christoffel
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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.
Analisis Spasial Persebaran COVID-19 di Indonesia Menggunakan Metode K-Means Clustering dan ESD Mario, Christoffel; Siahaan, Linda Natasya; Simanullang, Junitro Andreas; Simamora, Tabita Paulina
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 3 (2025): April 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15276145

Abstract

The COVID-19 pandemic, which began in March 2020, has had a significant impact on public health in Indonesia. Although case numbers have started to decline, understanding the spatial spread of the virus remains crucial for effective response efforts. Conventional analyses that rely solely on descriptive statistics often overlook spatial relationships between regions. This study combines Exploratory Spatial Data Analysis (ESDA) and K-Means Clustering to examine the spatial distribution of COVID-19 cases and group Indonesian provinces based on the number of cases, recovery rates, and mortality rates. The data used include Indonesias provincial shapefiles from GADM and COVID-19 case data from Data Wrapper. The analysis reveals three main clusters. Cluster one includes DKI Jakarta, West Java, and Central Java, characterized by high case numbers and mortality rates, with below-average recovery rates. Cluster two consists of East Java, North Sumatra, and South Sulawesi, with relatively low case numbers, very low recovery rates, and high mortality rates. Cluster three comprises 26 other provinces with lower case numbers, high recovery rates, and low mortality rates. These findings indicate that COVID-19 transmission in Indonesia is not spatially uniform, highlighting the need for targeted intervention in high-risk areas.
Analisis Faktor-Faktor yang Mempengaruhi Indeks Pembangunan Manusia di Provinsi Jawa Barat Menggunakan Regresi Linier Berganda Sinaga, Anita; Mario, Christoffel; Septianingtias, Indri Avisa
Socius: Jurnal Penelitian Ilmu-Ilmu Sosial Vol 2, No 12 (2025): July 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15696995

Abstract

Indeks Pembangunan Manusia (IPM) merupakan indikator penting dalam mengukur kualitas hidup masyarakat suatu daerah. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi IPM di Provinsi Jawa Barat dengan menggunakan metode regresi linier berganda. Data yang digunakan adalah data panel dari 27 kabupaten/kota selama periode 2022–2024, mencakup variabel dependen IPM dan enam variabel independen: PDRB per kapita, realisasi bantuan sosial, persentase rumah tangga dengan akses air minum layak, persentase penduduk miskin, angka partisipasi sekolah usia 19–23 tahun, dan umur harapan hidup. Pemodelan dilakukan secara bertahap melalui metode forward selection serta diuji menggunakan asumsi-asumsi klasik regresi. Hasil akhir menunjukkan bahwa seluruh variabel independen memiliki pengaruh signifikan terhadap IPM, dengan model akhir menjelaskan 89% variasi IPM (R² = 0,89). Penelitian ini memberikan kontribusi dalam pemahaman empiris terhadap faktor-faktor pembangunan manusia dan dapat dijadikan dasar penyusunan kebijakan pembangunan daerah yang lebih efektif dan tepat sasaran. 
Co-Authors Haliza, Putri Yusra Hondro, Yizhar Saputra Septianingtias, Indri Avisa Siahaan, Linda Natasya Simamora, Tabita Paulina Simanullang, Junitro Andreas Sinaga, Anita Syairal Fahmy Dalimunthe Tamara, Angga