SISTEM MONITORING DENYUT JANTUNG DENGAN METODE FUZZY LOGIC PADA PENDERITA HIPERTIROIDISME BERBASIS IOT

M. FIKRI FIRDAUS, . (2025) SISTEM MONITORING DENYUT JANTUNG DENGAN METODE FUZZY LOGIC PADA PENDERITA HIPERTIROIDISME BERBASIS IOT. Sarjana thesis, UNIVERSITAS NEGERI JAKARTA.

	Text Cover - M. Fikri Firdaus [1507521008].pdf Download (1MB)
	Text BAB I - M. Fikri Firdaus [1507521008].pdf Download (443kB)
	Text BAB II - M. Fikri Firdaus [1507521008].pdf Restricted to Registered users only Download (1MB) | Request a copy
	Text BAB III - M. Fikri Firdaus [1507521008].pdf Restricted to Registered users only Download (1MB) | Request a copy
	Text BAB IV - M. Fikri Firdaus [1507521008].pdf Restricted to Registered users only Download (2MB) | Request a copy
	Text BAB V - M. Fikri Firdaus [1507521008].pdf Restricted to Registered users only Download (428kB) | Request a copy
	Text Daftar Pustaka - M. Fikri Firdaus [1507521008].pdf Download (387kB)
	Text Lampiran - M. Fikri Firdaus [1507521008].pdf Restricted to Registered users only Download (2MB) | Request a copy

Abstract

Hipertiroidisme ditandai oleh peningkatan kadar hormon tiroid yang memicu takikardia dan tremor, sehingga efektifitas terapi β-blocker (propranolol) sangat bergantung pada dosis yang tepat. Penelitian ini mengembangkan sistem monitoring real-time berbasis Internet of Things (IoT) untuk mengukur denyut jantung (BPM) menggunakan sensor optik MAX30102 dan frekuensi tremor (Hz) menggunakan sensor MPU6050. Data sensor dikirim oleh mikrokontroler ESP32 ke platform Firebase, lalu diproses dengan metode Fuzzy Logic Mamdani untuk menentukan rekomendasi dosis propranolol. Model fuzzy logic memanfaatkan dua variabel input yaitu; denyut jantung (rendah, normal, tinggi) dan tremor (ringan, sedang, berat) dan menghasilkan tiga level ouput dosis propranolol (10 mg, 20 mg, 40 mg). Pengujian selama sepuluh hari mencakup kondisi aktivitas fisik, pasca konsumsi obat, kondisi istirahat, serta respons setelah penerapan rekomendasi. Validasi terhadap alat referensi menunjukkan rata-rata akurasi sensor MAX30102 sebesar 94,66% dan error 5,34% serta sensor MPU6050 sebesar 94,01% dan error 5,99%. Hasil eksperimen memperlihatkan bahwa sistem dapat menjaga denyut jantung di bawah 90 BPM dan meredam frekuensi tremor dibawah 5 Hz. Penerapan rekomendasi fuzzy logic menurunkan variasi denyut jantung dan intensitas tremor. Dengan demikian, sistem IoT fuzzy logic ini terbukti efektif meningkatkan keamanan terapeutik dan berpotensi mengurangi frekuensi kunjungan klinis pada penderita hipertiroidisme ***** Hyperthyroidism is characterized by elevated thyroid hormone levels that trigger tachycardia and tremor,rendering the efficacy of β-blocker therapy (propranolol) highly dependent on accurate dosing. This study presents the development of a real-time monitoring system based on the Internet of Things (IoT) to measure heart rate (BPM) via an optical MAX30102 sensor and tremor frequency (Hz) via an MPU6050 sensor. Sensor data are transmitted by an ESP32 microcontroller to the Firebase platform, where Mamdani fuzzy logic processing determines propranolol dose recommendations. The fuzzy logic model employs two input variables heart rate (low, normal, high) and tremor (mild, moderate, severve) and yields three output levels of propranolol dosage (10 mg, 20 mg, 40 mg). A ten day trial encompassing physical activity, post medication, rest, and post recommendation response scenarios was conducted. Validation against reference instruments demonstrated mean accuracies of 94,66% (error 5,34%) for the MAX30102 sensor and 94,01% (error 5,99%) for the MPU6050 sensor. Experimental results indicate that the system maintained heart rate below 90 BPM and suppressed tremor frequency below 5 Hz. Implemntation of the fuzzy logic recommendations reduced both heart rate variability and tremor intensity. These findings confirm that the IoT based fuzzy logic system effectively echances therapeutic safety and holds potential to decrease the frequency of clinical visits for patients with hyperthyroidism

Item Type:	Thesis (Sarjana)
Additional Information:	1). Rafiuddin Syam, S.T., M.Eng., Ph.D. ; 2). Drs. Rimulyo Wicaksono, M.M.
Subjects:	Teknologi dan Ilmu Terapan > Teknik Elektronika
Divisions:	FT > D IV Teknologi Rekayasa Otomasi
Depositing User:	M. Fikri Firdaus .
Date Deposited:	07 Aug 2025 07:57
Last Modified:	07 Aug 2025 07:57
URI:	http://repository.unj.ac.id/id/eprint/58840

Actions (login required)

View Item