Utilizing Data Mining Approach For Hypertension Diagnosis Classification

Utilizing Data Mining Approach For Hypertension Diagnosis Classification

• By Widodo, Pudji; Setyadi, Heribertus Ary; Wahyuningsih, Hartati Dyah; Sundari;
• Jurnal Nasional Terakreditasi
• 155
• 34-42

Hypertension is one of the factors contributing to the highest death rates from noncommunicable diseases in various countries. Every year, the number of hypertension sufferers
increases significantly. It is estimated that in 2025, the number of hypertension sufferers will reach
1.5 billion individuals. Data mining aims to identify patterns that can help in decision making,
classification, and prediction. One of the well-known algorithms or methods for classification is the
Support Vector Machine (SVM). The SVM method aims to find the best hyperplane or decision
boundary function that can separate two or more classes of data in the input space. This research
purpose is to determine the classification results and accuracy of the diagnosis of hypertension using
the SVM method. Eleven attributes used include age, smoking habits, physical activity, sugar
consumption, salt consumption, fat consumption, alcohol consumption, lack of fruit and vegetable
consumption, systolic and diastolic blood pressure. This research will utilize Jupyter Notebook tools
and Python programming language as research tools. The SVM method was trained with various
kernel attributes and hyperparameters to produce the best model. From the results it is known that
the RBF kernel used with parameters � = 100 and � = 0.1 produces an accuracy of 97.5% which is
the best model in classifying hypertension. From these results it can be concluded that the SVM
method is able to produce a very good classification of hypertension diagnosis and can provide a
diagnosis to detect hypertension early.

• Katakunci classification, data mining, hypertention, SVM
• URL https://publikasi.polije.ac.id/jtit/article/view/6002
• Penerbit Jurnal Teknologi Informasi dan Terapan (JTIT) Politeknik Negeri Jember, Jember Jawa Timur

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