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All Journal Jurnal Komputer Indonesia (JU-KOMI) Jurnal Kesehatan, Rekam Medis dan Farmasi (JUK-Medifa)
Manahan Tua Tinambunan
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Computer Science & IT Electrical & Electronics Engineering Engineering Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health

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Characteristics of Hypertension Patients in the Working Area of the Parlilitan District Health Center, Humbang Hasundutan Regency, North Sumatra Province, 2023 Manahan Tua Tinambunan; Mardiati Barus; Ance Siallagan
Jurnal Kesehatan, Rekam Medis dan Farmasi (JUK-Medifa) Vol. 3 No. 02 (2025): JUK-Medifa (Jurnal Kesehatan, Rekam Medis dan Farmasi), 2025
Publisher : SEAN Institute

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Abstract

Hypertension is an increase in blood flow that occurs in the human body and is a leading cause of death globally. Hypertension does not only affect the elderly but also individuals of productive age. It is also referred to as the “silent killer.” This study aims to describe the characteristics of hypertension patients in the working area of the Upt Health Center, Parlilitan District, Humbahas Regency, North Sumatra Province, in 2023. This study used a descriptive method. The sampling technique employed was total sampling, with a total of 86 respondents. The measurement tool used was an Observation Sheet. The results showed that respondents aged 55–65 years numbered 30 (34.9%), while those aged 26–35 years numbered 4 (4.7%). Based on gender, 46 respondents were male (53.5%) and 40 were female (46.5%). Based on education, 33 respondents (38.4%) had completed senior high school/vocational school, and 14 respondents (16.3%) had attended higher education. Based on occupation, 43 respondents (50.0%) were farmers, 12 (14.0%) were housewives, and 31 (36.2%) were civil servants. Regarding marital status, 84 respondents (97.7%) were married, while 2 respondents (2.3%) were unmarried. Regarding medication, 67 respondents (66.3%) did not consume hypertension medication, while 34 respondents (33.7%) did. Based on symptoms frequently experienced by respondents, 71 respondents (82.6%) reported dizziness, and 15 respondents (17.4%) reported pain. Based on the study results, most hypertension patients had blood pressure classified as hypertension grade II, totaling 40 respondents (50.5%), while the minority were in the prehypertension category, totaling 8 respondents (7.9%).
Patient Hypertension Modeling Using Decision Tree: Analysis of Age, Symptoms, Fatty Food Intake, Salt Intake, Medication Count, and Blood Pressure Using RapidMiner Manahan Tua Tinambunan; Sipra Barutu
Jurnal Komputer Indonesia (Ju-Komi) Vol. 3 No. 02 (2025): Jurnal Komputer Indonesia (JU-KOMI), April 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/ju-komi.v3i02.758

Abstract

Hypertension is a chronic disease characterized by persistently elevated blood pressure and remains a major global health problem. Various interacting factors, including age, salt and fatty food intake, medication use, and blood pressure, influence the risk and symptoms of hypertension. This study aims to identify patterns and characteristics of hypertension patients and determine the most influential factors using data mining techniques. A quantitative approach with the Decision Tree algorithm was applied using RapidMiner Studio. The analysis involved data preprocessing, model training and validation, and identification of influential variables. The Decision Tree analysis revealed that medication use is the main determinant of symptom patterns in hypertension. In patients not taking medication, symptoms were mainly influenced by salt intake and blood pressure, where low salt intake was associated with nausea and moderate salt intake with varied symptoms, especially headaches. In patients taking medication, symptom patterns were affected by the combination of salt and fatty food intake. High salt and fat consumption were associated with dizziness, while moderate intake was related to fatigue. Hypertension symptoms are determined not only by blood pressure but also by lifestyle factors and medication use. The Decision Tree model effectively identifies hierarchical relationships among these factors, providing valuable insights for healthcare professionals to design more targeted hypertension management and prevention strategies.
Co-Authors Ance Siallagan Mardiati Br Barus Sipra Barutu