MODEL LOG-LINEAR FAKTOR-FAKTOR YANG MEMPENGARUHI HIPERTENSI (STUDI KASUS: RSUD ABDOE RAHEM SITUBONDO)

  • IMAMUDDIN KAMIL Universitas Udayana
  • MADE SUSILAWATI Universitas Udayana
  • I PUTU EKA NILA KENCANA Universitas Udayana

Abstract

The purpose of this study was to determine the effect of the factors age, sex, obesity, family history (heredity), and smoking habits on hypertension status. The research data is secondary data obtained from the medical records of disease in hospitals in East Java Abdoe Rahem Situbondo the data of patients affected by hypertension stage I and II, with a sample size of 137 patients. Methods of data analysis using log-linear regression analysis. The result showed the best log-linear Model are: log mijklmn = U + U134(ikl) + U245(jlm) + U456(lmn) + U1246(ijln) + U12356(ijkmn), explained the factors that influence the risk of hypertension (U6), namely the factors that can not be changed such as gender ((U1), age ((U2), family history ((U3), while factors can be changed such as smoking habits ((U4), and obesity ((U5). Interactions also occur between the factors that influence the risk of hypertension, as shown in the model U134(ikl), namely gender, family history, and smoking habits. In the model U245(jlm)the factors age, smoking, and obesity among interacting factors that influence the risk of hypertension.

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Author Biographies

IMAMUDDIN KAMIL, Universitas Udayana
Jurusan Matematika, Fakultas MIPA
MADE SUSILAWATI, Universitas Udayana
Jurusan Matematika, Fakultas MIPA
I PUTU EKA NILA KENCANA, Universitas Udayana
Jurusan Matematika, Fakultas MIPA
Published
2012-09-16
How to Cite
KAMIL, IMAMUDDIN; SUSILAWATI, MADE; NILA KENCANA, I PUTU EKA. MODEL LOG-LINEAR FAKTOR-FAKTOR YANG MEMPENGARUHI HIPERTENSI (STUDI KASUS: RSUD ABDOE RAHEM SITUBONDO). E-Jurnal Matematika, [S.l.], sep. 2012. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/1788>. Date accessed: 10 aug. 2020. doi: https://doi.org/10.24843/MTK.2012.v01.i01.p015.
Section
Articles

Keywords

Log-linear models; best log-linear model; the factors of hypertension

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