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All Journal Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Madani: Multidisciplinary Scientific Journal Tashdiq: Jurnal Kajian Agama dan Dakwah
Tamara, Angga
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ANALISIS FAKTOR PENYEBAB PENYAKIT JANTUNG MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA) Manullang, Sudianto; Kairani, Nerli; Sinaga, Marlina Setia; Hutapea, Brian; Nadya, Fauza; Br Barus, Jesika Casadae Wanda; Tamara, Angga; Silaban, Dewi Fortuna
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i3.732

Abstract

Factor analysis is an important method in research to identify the underlying structure of complex data. Heart disease is a disease caused by a disturbance in the coronary blood vessels that causes narrowing and blockage so that it can interfere with the body's energy transportation process and also cause an imbalance between oxygen demand and oxygen supply. Various factors such as age, gender, smoking, etc. have an important role for a person to get heart disease. This study aims to analyze the factors that cause heart disease using the Principal Component Analysis (PCA) method. PCA is used to identify and reduce the dimensions of heart disease factor data. The data used in this study were obtained from journals and consisted of 7 variables. PCA successfully identified 2 main factors that explained 75% of the total variance in the data. Through dimensionality reduction, the number of variables was successfully reduced from 7 factors to 2 factors without significant information loss. This study found that the PCA method was effective in reducing the dimensionality of the data and identifying the main factors underlying the data.
ANALISIS FAKTOR-FAKTOR PENYEBAB PERCERAIAN DI PROVINSI SUMATERA UTARA DAN KABUPATEN DELI SERDANG Nurmayani; Pulungan, Zakiy Maulana; Aqil, Muhammad Fachri; Harahap, Adi Gunawan; Tamara, Angga; Lubis, Hafiz Khalik; Lubis, M. Shadri Ismaun; Triono, Wira
Tashdiq: Jurnal Kajian Agama dan Dakwah Vol. 12 No. 4 (2025): Tashdiq: Jurnal Kajian Agama dan Dakwah
Publisher : Cahaya Ilmu Bangsa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4236/tashdiq.v12i4.12292

Abstract

Penelitian ini bertujuan untuk menganalisis faktor-faktor penyebab perceraian di Provinsi Sumatera Utara dan Kabupaten Deli Serdang selama periode 2018-2023. Data sekunder diperoleh dari Kantor Urusan Agama (KUA) Kecamatan Percut Sei Tuan dan Badan Pusat Statistik (BPS) Provinsi Sumatera Utara. Metode penelitian yang digunakan adalah kualitatif deskriptif dengan analisis statistik untuk mengidentifikasi tren dan distribusi perceraian berdasarkan faktor penyebabnya. Hasil penelitian menunjukkan bahwa perselisihan dan pertengkaran terus-menerus menjadi faktor dominan penyebab perceraian, berkontribusi lebih dari 70% terhadap total kasus di kedua wilayah. Faktor ekonomi juga memainkan peran signifikan, terutama dalam memperburuk hubungan rumah tangga. Di Provinsi Sumatera Utara, angka perceraian tertinggi terjadi pada tahun 2020 dan 2021 dengan 17.270 kasus, sedangkan di Kabupaten Deli Serdang, puncak perceraian terjadi pada tahun 2021 dengan 2.973 kasus. Analisis ini mengindikasikan bahwa ketahanan keluarga di kedua wilayah masih rentan terhadap konflik domestik dan tekanan ekonomi.
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