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All Journal Al-Hayat: Journal of Islamic Education Jurnal Matematika UNAND LAN TABUR: Jurnal Ekonomi Syari’ah Infotek : Jurnal Informatika dan Teknologi Tsaqafatuna: Jurnal Ilmu Pendidikan Islam Al-tsaman : Jurnal Ekonomi dan Keuangan Islam Wahana Dedikasi : Jurnal PkM Ilmu Kependidikan Jurnal Pengabdian Kepada Masyarakat Patikala Mabahits Menara Pengabdian Nanggroe: Journal Of Scholarly Service Nanggroe: Journal of Scholarly Service Jurnal Paramaedutama Al-Balad : Jurnal Hukum Tata Negara dan Politik Islam Science, Technology, and Communication Journal Proceeding of International Conference on Humanity Education and Society PANDALUNGAN : Jurnal Pengabdian kepada Masyarakat Jurnal Dinamika Manajemen LAN TABUR: JURNAL EKONOMI SYARIAH
Hamdi, Muhammad
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Journal : Science, Technology, and Communication Journal

 1 
Modeling of terahertz radiation absorption temperature distribution in biological tissue of a cattle using Simulink-MATLAB model Kurnia, Dewi; Hamdi, Muhammad; Muhammad, Juandi; Saktioto, Saktioto; Yupapin, Preecha; Abdullah, Hewa Yaseen
Science, Technology and Communication Journal Vol. 1 No. 2 (2021): SINTECHCOM Journal (February 2021)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v1i2.6

Abstract

Terahertz radiation (THz) has interesting and effective properties in the field of biomedical imaging techniques, this is because of its ability to interact easily, is not ionized, and does not damage biological tissue. The purpose of this study was to determine the effect of THz radiation power density on temperature distribution and heat production in bovine biological tissue consisting of skin, fat, and muscle using a modeling approach. This study uses biophysical computation techniques with the Simulink-MATLAB model in the 0.1 – 1 THz frequency range, 50 – 150 mW power, and 5 – 25 mW/mm3 power density. Temperature distribution modeling is carried out in two ways, namely with different power densities and variations in the circumference of the THz radiation source. The results showed that the higher the power density used, the greater the absorbed radiation energy with increasing temperature. This causes the temperature distribution in the biological tissue to be wider and the production of heat in the tissue will increase. The results of imaging analysis of temperature distribution to depth in bovine biological tissue, show that fat tissue has less heat production compared to other tissues. The comparison of experimental data and modeling results shows an error percentage of 1.09%.
Analysis of non-destructive testing ultrasonic signal for detection of disabled materials based on the Simulink-MATLAB Mathematica computation method Febrianti, Ade; Hamdi, Muhammad; Muhammad, Juandi
Science, Technology and Communication Journal Vol. 1 No. 2 (2021): SINTECHCOM Journal (February 2021)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v1i2.27

Abstract

In this paper, an ultrasonic non-destructive test (NDT-UT) has been carried out on steel using the Simulink-MATLAB Mathematica computation method. This study aims to analyze the NDT-UT output signal for material defect detection using secondary data as the first sample. The sample is then analyzed using the fast Fourier transform (FFT) method to produce a spectrum waveform and image thermography. It can be seen that there is a decrease in signal height from 1 a.u to 0.55 a.u. The first sample waveforms were used to analyze the second sample, third sample, and fourth sample, and all the samples had different defects. The results of the sample analysis are in the form of a thermographic image that shows the temperature level based on the distribution of red (R), green (G), and blue (B) images on the sample surface. The NDT-UT output signal produces a sinusoidal wave similar to the results of the Simulink-MATLAB modeling analysis on the initial input echoes and the back wall, with a percentage inequality of 10%. Then validated the sinusoidal signal from the NDT-UT which gave a percentage of inequality between 0% – 42%. More complex or irregular defects result in a larger percentage or vice versa.
Electrocardiogram signal patterns detection of myocardial ischemia rhythm using an artificial neural network based on MATLAB/Simulink Arianto, Yendra; Hamdi, Muhammad; Meyzia, Bunga
Science, Technology and Communication Journal Vol. 3 No. 1 (2022): SINTECHCOM Journal (October 2022)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v3i1.222

Abstract

This study aims to design a computer program to detect myocardial ischemic heart defects through electrocardiogram (ECG) signal patterns and their accuracy. Myocardial ischemia is a heart disorder caused by the narrowing of the blood vessels in the walls of the heart. The method used is a backpropagation-based artificial neural network (ANN) based on MATLAB/Simulink. The input data is trained to recognize the target pattern of the ECG signal based on the potential and time in the ST segment. The optimal weight of the results of the ANN backpropagation algorithm is used in the process of testing the ECG signal pattern to obtain the ANN output. The ANN output was analyzed for potential depression or elevation to identify normal heart or myocardial ischemia. The results of the training show that from several architectures that have been tested, the optimal ANN architecture is 1 hidden layer with 11 hidden units. These results are obtained from the epoch parameter and the mean square error (MSE) value as well as the accuracy of each architecture. The backpropagation ANN learning process requires 8 epochs to achieve the performance goal with MSE 4.03 × 10-9. The system can recognize target patterns with a training accuracy of 99.82%. The test results of the ANN program identification system can detect myocardial ischemia and normal heart abnormalities with an accuracy of 86.7%. Some data were not detected because the ANN output did not meet the criteria for cardiac ischemia or normal myocardium on the ECG signal. Based on the accuracy of the ANN program identification system, the detection of myocardial ischemia rhythm ECG signal patterns using ANN can be said to work well.
Co-Authors Abdul Aziz Abdullah, Hewa Yaseen Adi Putri, Silvia Adzkia, Legabina Alridho Lubis, Muhammad Arianto, Yendra Arifandi, Moh Zainal Aulia, Usma Cahyono, Dimas Nur Dasuki, Mohammad Des Welyyanti Dewi Kurnia DIAN LESTARI Diantoro, Femba Akris Dimas, Fatwa Erpidawati, Erpidawati Fadhlya Adri, Rantih Fadila, Nailatul Febrianti, Ade Ferdiansyah, Supardi Fikri, Muhammad Ali Furoidah, Asni Geaparga, Genny H.S, Dovi Iwan Musthofa Habibillah, Dovi Iwan Musthofa Hamroni, Hamroni Harianto Harianto Ikawati, Retty Ikhlas Pratama Sandy Imam Bukhori Jamhari, Djauhar Jauharoh, Ummu Lum’atil Juandi Juandi Latifa Putri, Tasya Lisa, Tia Mannan, Ahmad Mizan Rosyadi Abdul Jalil Masithoh, Fitria Nur Meyzia, Bunga Mu'awanah, Mu'awanah Mu'awwanah, Uliyatul Muhammad Ferdiansyah, Muhammad Muhammad Zulfikar Mursidah Mursidah, Mursidah musthofa H, Dovi iwan Mutiara Dewi, Mutiara Mu’awanah, Ulyatul Rani Safitri Rasimin Refindra Wijaya, Tiara Rizqo, Imam Rohmah, Lailiyatur Rully Andi Yaksa, Rully Rusmini Rusmini saddad, Anwar Saktioto Saktioto Setiana, Iffa Soni Redha, Pratiwi Sugitanata, Arif Susanti, Elsi Syaddad, Anwar Syarofi, Muhammad Wijaksono, Indra Yupapin, Preecha