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All Journal SCIENCE ELECTRO Jurnal Ilmiah Teknik Informatika dan Komunikasi
Nabila Amelia
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Computer Science & IT Electrical & Electronics Engineering Energy

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STUDI ARITMIA PADA DATA DISKRIT ELECTROCARDIOGRAM (ECG) UNTUK MENENTUKAN SINYAL PQRST DENGAN METODE EKSTRIMA Nabila Amelia; M. Jasa Afroni; Bambang Minto Basuki
SCIENCE ELECTRO Vol 12, No 2 (2020): Internet of Things Pada Bidang Elektro
Publisher : Science Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.893 KB)

Abstract

Hasil pemeriksaan ECG digunakan untuk mengetahui nilai puncak PQRST. Setiap siklus sinyalECG memiliki gelombang yang terdapat Peak PQRST (mS), durasi interval PR, QT, ST, dan QS (mV),dan durasi segmen PR dan ST (mV). Informasi peak amplitude yang jumlahnya besar dari hasil rekamansinyal ECG menyebabkan lamanya waktu untuk memeriksa, karena umumnya masih menggunakan caramanual, yakni menghitung kotak-kotak kecil yang terdapat di bagian latar belakang pada kertas yangdikhususkan untuk ECG yang dilalui oleh gelombang ECG. Dalam penelitian ini akan dibuat programpembaca nilai sinyal PQRST dengan meggunakan metode Ekstrima agar proses deteksi parameter sinyalmenjadi lebih mudah dan efektif menggunakan Matlab. Hasil yang diperoleh berupa nilai dari PeakPQRST dengan rata-rata untuk titik P -7,365, Q -92,519, R -6,150 S -133,354, dan untuk T -3,598, durasiinterval dan durasi segmen, dengan keluaran nilai yang akurat. Metode ini bukan untuk menggantikanperan tenaga medis, tetapi diharapkan dapat membantu tenaga medis untuk menganalisis sinyal ECG.Kata kunci : Electrocardiogram, Peak PQRST, durasi segmen, durasi interval, Matlab
Sistem Pakar Diagnosa Penyakit Tanaman Padi Menggunakan Metode Forward Chaining Ismail Ismail; Hermi Rani; Nabila Amelia
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 6 No. 1 (2026): Maret : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v6i1.1752

Abstract

Rice is one of the leading commodities in Indonesia that has a strategic role in maintaining national food security. One of the main factors that hinders the increase in rice crop production is disease attacks, which can be caused by pathogens, host plant conditions, or less supportive environmental factors. The process of diagnosing rice crop diseases generally requires special expertise, knowledge, and experience from experts in the field of agriculture, the availability of which is still limited in some areas. Therefore, technology-based solutions are needed to assist farmers in making quick and accurate diagnoses. This research aims to build a mobile-based expert system that is able to diagnose 13 types of rice plant diseases based on 43 symptoms, by referring to the knowledge of three experts. The reasoning method used is forward chaining, while the uncertainty calculation method uses Shafer's Dempster theory. The results of the black box test showed that the expert system had a functional suitability rate of 100% based on all test scenarios carried out. In addition, the results of the theoretical calculation test showed that the system calculation was in accordance with the results of manual calculations. The accuracy test of the system on 30 test cases obtained an accuracy rate of 81.11%, so the system is considered quite reliable as a tool to diagnose rice plant diseases.
Co-Authors Bambang Minto Basuki Hermi Rani Ismail Ismail Mohammad Jasa Afroni