Cindy Kaillah Nurjanah, . (2025) RANCANG BANGUN ALAT PEMANTAUAN TEKANAN DARAH DENGAN METODE FUZZY SUGENO UNTUK DETEKSI DINI HIPERTENSI BERBASIS INTERNET OF THINGS. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Hypertension, or high blood pressure, is a global health issue with a high prevalence, including in Indonesia, where it affects approximately 30.8% of the population. Known as “The Silent Killer,” hypertension often presents no symptoms and is typically detected only through routine medical examinations. This study aims to develop an Internet of Things (IoT)-based early detection system for hypertension using the Fuzzy Sugeno classification method with three main input parameters: systolic blood pressure, diastolic blood pressure, and age. The system utilizes the MPX5700AP pressure sensor, which achieved an accuracy of 96.47% for systolic and 95.10% for diastolic blood pressure measurements, along with the MAX30100 sensor, which demonstrated a 96.01% accuracy for heart rate monitoring. Measurement results are displayed in real time with average data transmission times of 1.60 seconds on the LCD, 3.07 seconds on the local website, and 4.57 seconds via Telegram. The system classifies blood pressure conditions into four categories: Normal, Pre-hypertension, Hypertension Stage 1, and Hypertension Stage 2, with an overall classification accuracy of 94.55%, and average precision, recall, and F1 Score of 97%, 95.31%, and 96.15%, respectively. This system is expected to serve as an effective tool for early hypertension detection.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | No.Panggil: 2110314049 Pembimbing 1: Ni Putu Devira Ayu Martini Pembimbing 2: Muhamad Alif Razi Penguji 1: Didit Widiyanto Penguji 2: Silvia Anggraeni |
| Uncontrolled Keywords: | Blood Pressure, ESP32, Fuzzy Sugeno, Hypertension, Telegram |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Teknik > Program Studi Teknik Elektro (S1) |
| Depositing User: | CINDY KAILLAH NURJANAH |
| Date Deposited: | 20 Aug 2025 04:11 |
| Last Modified: | 20 Aug 2025 04:11 |
| URI: | http://repository.upnvj.ac.id/id/eprint/39623 |
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