Application of the K-Nearest Neighbor Method for Classification of Hypertension Diseases (Case Study: Stabat Health Center) - Sari, Indah Kelana; Pardede, A M H; Simanjuntak, Magdalena (Yayasan Kita Menulis, 2024)
Globally, the WHO (World Health Organization) estimates that non-communicable diseases cause about 60% of deaths and 43% of diseases worldwide. Hypertension is a disease that occurs due to an increase in blood pressure in humans. It is difficult to know if a person has hypertension, without measuring the patient's blood pressure. According to the American Heart Association (AHA), the number of Americans over the age of 20 suffering from hypertension has reached 74.5 million, but nearly 90-95% of cases have no known cause. It is estimated that about 80% of the increase in hypertension cases will occur mainly in developing countries by 2025, from 639 million cases in 2000. This number is expected to increase to 1.15 billion cases in 2023. This study uses a quantitative approach with experimental methods to test the application of K-Nearest Neighbor (KNN) in the classification of hypertension diseases at the Stabat Health Center. The description of the results obtained is to make the right decision regarding when and how to treat the disease to prevent the worst possibility for patients by classifying the severity of hypertension both in normal circumstances, prehypertension, stage 1 hypertension, and stage 2 hypertension. The results of the trial show that the KNN model is able to provide accurate predictions based on patient history data available at Stabat Health Center.