Aplication Algorithm Learning Vector Quantization for Classification of Hypertention in Padang Laweh Health Center

Abstract

Hypertension is a health condition characterized by blood vessel disorders, in which there is a chronic increase in blood plessure of 140/90 mmHg. There are several factors that influence hypertension, including unhealthy eating patterns, lack of physical activity, smoking, stress and excess weight. Hypertension does not show clear symptoms, but it has the potential to cause other diseases such as heart failure, stroke, and premature death. Therefore, a study was conducted to classify the risk of hypertension based on hypertension diagnoses at the Padang Laweh Health Center, Dharmasraya Regency, using the Learning Vector Quantiazation (LVQ) Algorithm. The advantage of LVQ is its ability to achieve high accuracy in processing data with numerous numerical and categorical features. The analysis results show that the use of the Learning Vector Quantization Algorithm on the test data produces very good accuracy, namely 95.17% correct classification of hypertensive patients