Design of Application to Predict Someone Suffering Hypertension Using Data Mining

Abstract

Hypertension is one of the diseases of blood vessel disorders. In Indonesia, people with hypertension disease increased by 3.6% every year. The occurrence of hypertension increases due to the lack of care of the public for health, as well as the lack of time to consult a specialist or an expert. The purpose of this study (1) the data obtained can be used to predict a person suffering from hypertension. (2) Applications are made easy to use and have high accuracy prediction. The method used in this research is data mining with Naïve Bayes Classification method which is a classification method using probability and statistic. In collecting data required for Data Mining, researcher giving questionnaires to patients who visited hospital X for 3 weeks with questionnaire attributes that contains age, sex, weight, height, smokers, type of cigarette, the number of cigarettes, the consumption of alcoholic beverages, physical, sleep hours, meat consumption, vegetable consumption, salt level, history of father's hypertension, history of maternal hypertension. Conclusion (1) by using Data Mining, the patient can immediately find out whether the patient is suffering from hypertension based on the lifestyle he/she has. (2) Applications that have been developed can be used and has a fairly high accuracy of 88% and has a sensitivity of 77%, and 96% of specificity. (3) The use of Naïve Bayes to predict a person suffering from hypertension can be used because it has a high accuracy of 88%.