KLASIFIKASI KEJADIAN HIPERTENSI DENGAN METODE SUPPORT VECTOR MACHINE (SVM) MENGGUNAKAN DATA PUSKESMAS DI KOTA BANDAR LAMPUNG

Autor: Indah Pasaribu, Favorisen Rosyking Lumbanraja, Dewi Asiah Shofiana, Aristoteles Aristoteles
Rok vydání: 2021
Zdroj: Jurnal Pepadun. 2:183-190
ISSN: 2774-3403
DOI: 10.23960/pepadun.v2i2.56
Popis: Hypertension is a condition in which a person experiences an increase in blood pressure above the normal value which causes pain and even death. Normal human blood pressure is 120/80 mmHg. Patients with hypertension cannot be cured, but prevention and control can be done. The hypertension cases are always increasing in Indonesia. The Bandar Lampung City Health Service stated that hypertension is a disease that always ranks in the top ten diseases in Bandar Lampung City. Diagnosis of hypertension is currently manually performed by requiring a lot of energy, materials, and time. Based on the condition, there is an idea to apply the field of biomedical data analysis to help diagnosing hypertension using the support vector machine (SVM) method in Bandar Lampung City. This study classifies and measures the accuracy of the support vector machine method in hypertension. The data comes from five health centers in Bandar Lampung City from 2017 to 2019 with 10-fold cross validation data sharing. The kernels used are linear, gaussian, and polynomial kernels. This study successfully classifies hypertension sufferers in Bandar Lampung City. The result of the highest feature correlation analysis is 0.90. The results of the classification using the support vector machine method get the highest accuracy, which is 99.78% on the gaussian kernel.
Databáze: OpenAIRE