The Relationship Between Age, Parity, Ideal Weight, and Blood Pressure in Diagnosing Hypertension in Pregnant Women Using The K-Means Algorithm
Abstract
Hypertension is one of the health problems that often arise during pregnancy and can cause complications in 2-3% of pregnancies. Hypertension In Pregnancy (HDK) is defined as a blood pressure of ≥140/90 mmHg in two or more measurements. Data mining is a combination of a number of computer science disciplines that is defined as the process of discovering new patterns from very large data sets. By looking at records on Age, IMT, Parity / Gravidity, and Blood Pressure and analysis with K-Means clustering, it can be seen that the similarity of values of the above variables ultimately forms patterns related to hypertension in pregnant women. The clustering process using 5 clusters according to the elbow chart analysis. In this study, it was seen that the variable Blood Pressure is the same pattern and often appears in each cluster. While hypertension occurs in 1 cluster out of 5 existing clusters.
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