Analysis of Hypertension Disease using Logistic and Probit Regression

Open

D.I. Ruspriyanty, A. Sofro

2018 Journal of Physics: Conference Series Vol. 1108 Issue 1 Conference paper Cited by 15

Abstract

Hypertension (high blood pressure) is when blood pressure has reached or exceeded 140 mmHg (systole) and 90 mmHg (diastole). Suspected factors of the disease are age, obesity, education, partner status, and occupation. In this paper, we analyze models for determining high-risk factors of hypertensive disease. The results show that education and partner status are a significant factor affecting the disease. The Akaike Information Criterion value (AIC) of the logistic model is 118.64 and the probit model is 118.79. Therefore, the performance of a logistic model is better than probit due to providing the smaller value of AIC. © Published under licence by IOP Publishing Ltd.

Affiliations

Mathematics Department, Universitas Negeri Surabaya, Ketintang-Surabaya-East-Java, 60231, Indonesia