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All Journal Kitektro JURNAL NASIONAL TEKNIK ELEKTRO Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) Journal of Electronics, Electromedical Engineering, and Medical Informatics International Journal of Engineering, Science and Information Technology Jurnal Rekayasa elektrika Jurnal INFOTEL Tashdiq: Jurnal Kajian Agama dan Dakwah jes Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Pengabdian Rekayasa dan Wirausaha
Muhammad Irhamsyah
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Religion Aerospace Engineering Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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PERANCANGAN ANTENA MICROSTRIP RECTANGULAR PATCH ARRAY 4 ELEMEN UNTUK APLIKASI LTE Muhammad Reza Syahputra; Syahrial Syahrial; Muhammad Irhamsyah
Jurnal Komputer, Informasi Teknologi, dan Elektro Vol 2, No 4 (2017)
Publisher : Universitas Syiah Kuala

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Abstract

Tingkat kesuksesan kinerja sebuah sistem atau bagian dari antena sangatlah penting. Untuk menentukan kinerja dari parameter, maka harus dilakukan analisis terhadap tingkat kesuksesan kinerja dari parameter antena microstrip rectangular patch array. Antena mikrostrip rectangular merupakan antena dengan bentuk patch persegi panjang. antena mikrostrip array merupakan pengembangan dari antena mikrostrip biasa yang terdiri dari beberapa elemen peradiasi yang membentuk suatu jaringan dan mendesain antena mikrostrip patch rectangular array empat elemen untuk aplikasi LTE 1.8 GHz. Dalam perancangan ini antena mikrostrip dibangun menggunakan bahan Epoxy fiberglass FR-4 dengan konstanta dielektrik (εr) = 4,5, ketebalan lapisan dielektrik (h) = 0,0016 m = 1,6 mm dan Loss tangent = 0,018. Teknik pencatuan yang akan digunakan adalah teknik Microstrip Line Feed. Perancangan dan simulasi menggunakan bantuan simulasi antena. Pada penelitian ini menunjukkan bahwa perancangan antena mikrostrip dengan syarat VSWR 1 sampai 2, Return Loss -10 dB, gain 2 dBi dan pola radiasi omnidirectional. Pada frekuensi 1800 MHz didapatkan nilai return loss -26.680 dB, VSWR 1.097, Gain 6.787 dBi, Bandwidth 24.65 MHz dan pola radiasi omnidirectional. Dengan demikian antena dapat bekerja dengan baik
ANALISIS PERANCANGAN ANTENA MIKROSTRIP PATCH SEGITIGA ARRAY UNTUK APLIKASI WLAN 2,4 GHZ Ega Aulia Sarfina; Syahrial Syahrial; Muhammad Irhamsyah
Jurnal Komputer, Informasi Teknologi, dan Elektro Vol 2, No 2 (2017)
Publisher : Universitas Syiah Kuala

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Abstract

Antena merupakan bagian penting dalam sistem komunikasi wireless. Antena mikrostrip array memiliki bandwidth dan gain yang lebih besar dibandingkan antenna mikrostrip tunggal. Pada penelitian ini membahas tentang bagaimana menghitung dan mendesain antena mikrostrip patch segitiga array untuk aplikasi WLAN 2,4 GHz. Antena mikrostrip ini dibuat menggunakan Bahan Epoxy fiberglass FR-4 dengan konstanta dielektrik (εr)=4,4, ketebalan lapisan dielektrik (h) = 1,6 mm dan loss tangent = 0,02. Teknik pencatuan yang digunakan adalah teknik Microstrip Line Feed. Perancangan dan simulasi menggunakan bantuan software Advanced Design System (ADS). Pada hasil penelitian, menunjukan perancangan antena mikrostrip patch segitiga array yang dilakukan sudah memenuhi syarat untuk diaplikasikan pada WLAN 2,4 GHz dengan syarat VSWR 1 sampai 2, return loss -9.54 dB. Kata Kunci— Antena, Mikrostrip Array, Patch Segitiga, ADS, WLAN.
Studi Perbandingan HSDPA pada Telkomsel Flash Dan IndosatM2 Di Kota Banda Aceh Muhammad Irhamsyah; Putri Rizky Febriani
Jurnal Rekayasa Elektrika Vol 9, No 2 (2010)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (323.408 KB) | DOI: 10.17529/jre.v9i2.169

Abstract

HSDPA adalah sebuah protocol komunikasibergerak yang berteknologi 3,5G (third generation) yangtermasuk dalam keluarga teknologi High Speed PacketAccess (HSPA) yang mampu meningkatkan kecepatantransfer data dan kapasitas data lebih besar pada jaringanyang berbasis Universal Mobile Telecomunication System(UMTS). HSDPA mendukung kecepatan downlink sebesar1,8 Mbps, 3,6 Mbps, 7,2 Mbps dab 14,4 Mbps.Dalam penelitian ini akan dibandingkan layanan HSDPAdari TELKOMSEL FLASH dan INDOSAT IM2 dari satulakokasi ke lokasi lainnya untuk setiap perbedaan waktu danbesar kapasitas datanya.Hasilnya di peroleh kecepatan akses data Telkomsel FLASHsedikit lebih unggul dari IM2. Telkomsel FLASH memilikikecepatan akses maksimum sampai 3,2 Mbps dan INDOSATIM2 mencapai 2,6 Mbps. Kedua operator selular ini telahmemiliki akses kecepatan tinggi yang cukup bersaing dandapat memberikan kepuasan tersendiri untuk masing-masing konsumennya.
Sistem Pemantau dan Pengontrol Suhu dan pH Air Otomatis pada Budidaya Ikan Gabus Meutia, Ernita Dewi; Utama, Muhammad Yoga; Munadi, Rizal; Irhamsyah, Muhammad
Journal of Engineering and Science Vol. 2 No. 2 (2023): July-December 2023
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jes.v2i2.143

Abstract

Maintaining the temperature and pH of water in fish farming is important to maintain the survival of the commodities being cultivated. Snakehead fish as one of the freshwater fish cultivation commodities, live in a temperature range of 25° to 32°C, and a pH of 4,5 to 6. Changes in temperature and pH due to  differences in day and night and weather conditions can be mortal for the fish. To help the fish farmers maintain water quality, in this research a prototype of IoT based temperature and pH monitor and control was built using Arduino microcontroller, that  can be accessed through a mobile application on Android smartphone. The test results show that the prototype has successfully control the temperature by turning the heater on when it dropped below 25°C, turned the acid solution pump on when the pH felt below 4.5, and alkaline solution pump when pH was above 6. Continuous sensor readings are able to  maintain the stability of water quality.
Object Segmentation in Stunted Face Images using Deeplabv3+ with Resnet-50 Yunidar, Yunidar; Melinda, Melinda; Irhamsyah, Muhammad
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1253.2024

Abstract

Stunting is the impaired growth and development that children experience from poor nutrition, repeated infection, and inadequate psychosocial stimulation. This study explores the impact of data preprocessing, specifically using DeepLabV3+ segmentation, on the performance of ResNet-50 in classifying stunting and non-stunting facial images. Initially, ResNet-50 achieved 99% accuracy and a 3.22% loss with the unsegmented dataset. By applying DeepLabV3+ to remove irrelevant features and backgrounds, the model's performance improved to a perfect 100% accuracy and a reduced loss of 0.45%. These results underscore the importance of high-quality data preprocessing in enhancing model precision and reliability. The findings have significant implications for practical applications, particularly in medical imaging, where improved diagnostic accuracy can benefit patient outcomes. Further research is recommended to explore additional preprocessing methods and their effects on model performance across diverse domains. This study highlights the transformative potential of effective data preprocessing in optimizing deep learning models for more accurate and reliable machine learning solutions.
Intelligent Tuberculosis Detection System with Continuous Learning on X-ray Images A'yuni, Qurrata; Nasaruddin, Nasaruddin; Irhamsyah, Muhammad; Azhary, Mulkan; Roslidar, Roslidar
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 1 (2025): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i1.572

Abstract

Tuberculosis (TB) has become a global health threat with millions of cases each year. Therefore, rapid and accurate detection is needed to control its spread. The application of artificial intelligence, especially Deep Learning (DL), has shown great potential in improving the accuracy of TB detection through DL-based X-ray image analysis. Although many studies have developed X-ray image classification models, very few have integrated them into web or mobile platforms. In addition, the models integrated into these platforms generally do not apply continuous learning methods so that model performance cannot be updated. Thus, it is necessary to build an intelligent system based on a web application that integrates the ResNet-101 model for TB detection in X-ray images. This system utilizes continuous learning methods, allowing the model to automatically update itself with new data, thereby improving detection performance over time. The results showed that before continuous learning, the model successfully classified all TB images correctly, but was only able to classify two normal images correctly, resulting in an accuracy of 62.5%. After manual continuous learning, the model showed an increase in accuracy to 71.4%, with better ability to recognize normal images, although there was a slight decrease in performance in detecting TB.
ANALISIS AN NIDA’ DALAM AL QURAN SURAH AL A’RAF AYAT 26: SERUAN ALLAH PADA WANITA UNTUK MENUTUP AURAT Pransetia, Arya Handika; Muhammad Irhamsyah
Tashdiq: Jurnal Kajian Agama dan Dakwah Vol. 11 No. 3 (2025): Tashdiq: Jurnal Kajian Agama dan Dakwah
Publisher : Cahaya Ilmu Bangsa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4236/tashdiq.v11i3.11018

Abstract

Penelitian ini menganalisis konsep An-Nida' dalam Al-Qur'an, khususnya dalam Surah Al-A'raf ayat 26, yang mengandung seruan Allah kepada umat manusia terkait kewajiban menutup aurat. Ayat ini diawali dengan seruan "Ya Bani Adam" yang ditujukan kepada seluruh keturunan Adam sebagai bentuk peringatan dan pengingat tentang pentingnya menutup aurat. Melalui pendekatan tafsir tematik dan analisis linguistik, penelitian ini mengkaji makna dan implikasi seruan tersebut, terutama dalam konteks kewajiban menutup aurat bagi wanita. Hasil analisis menunjukkan bahwa An-Nida' dalam ayat ini bukan hanya panggilan biasa, melainkan sebuah seruan yang menekankan aspek kesucian, kehormatan, dan ketaatan dalam berpakaian sesuai syariat. Ayat ini juga menunjukkan perhatian khusus Allah terhadap manusia agar menjaga fitrah dan kehormatan diri melalui pakaian yang menutupi aurat. Dengan demikian, penelitian ini menegaskan pentingnya menutup aurat sebagai bagian dari manifestasi ketaqwaan dan kepatuhan terhadap perintah Allah.
Classification of Arrhythmia Electrocardiogram Signals Using Kernel Principal Component Analysis and Naive Bayes Melinda, Melinda; Farhan; Irhamsyah, Muhammad; Miftahujjannah, Rizka; D Acula, Donata; Yunidar, Yunidar
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2219

Abstract

Arrhythmia is a cardiovascular disorder commonly detected through electrocardiogram (ECG) signal analysis. However, classifying arrhythmias based on ECG signals remains challenging due to signal complexity and individual variability. This study aims to develop a more accurate and efficient method for arrhythmia classification. The proposed method utilizes Kernel Principal Component Analysis (KPCA) and the naïve Bayes algorithm to classify arrhythmic ECG signals. KPCA is chosen for its ability to reduce data dimensionality, facilitating the processing of complex ECG signal and improving classification accuracy by minimizing noise. The naïve Bayes algorithm is chosen for its simplicity and computational speed, as well as its effective performance, even with limited data. ECG signals are processed using KPCA to reduce data dimensionality and extract relevant features. Subsequently, the naïve Bayes algorithm is then applied to classify the ECG signals into four categories: Premature Atrial Contraction (PAC), Premature Ventricular Contraction (PVC), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB).  The model's performance is evaluated using metrics such as accuracy, sensitivity, specificity, precision, and F1-score. The naïve Bayes model achieves an overall accuracy of 97.67%, with the highest performance observed in the RBBB class at 99.33%. Additionally, the F1-scores across all classes range from 96.62% to 98.57%, demonstrating the model's capability in detecting arrhythmias effectively. These results indicate that the combination of KPCA and naïve Bayes is effective for arrhythmic ECG signals classification.
Implementation of Discrete Wavelet Transform and Xception for ECG Image Classification of Arrhythmic Heart Disease Patients Irhamsyah, Muhammad; Melinda, Melinda; Yunidar, Yunidar; Muttaqin, Ikram; Zakaria, Lailatul Qadri
JURNAL INFOTEL Vol 17 No 2 (2025): May
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i2.1341

Abstract

The electrocardiogram (ECG) is one of the most important methods in the process of diagnosing heart disease. Visualizes the voltage and time relationship of the electrical activity of the heart. Cardiovascular or heart disease can be classified into several types, one of which is arrhythmia, a condition that involves changes in heartbeat rhythm, either too fast or too slow at rest. This study aims to develop a cardiac arrhythmia classification model using Deep Wavelet Transform (DWT) and Xception. It was evaluated on 2,200 spectrogram samples from the MIT-BIH dataset, containing normal and arrhythmia classes. The process compared epochs 30, 50, and 100 with learning rates of 0.001 and 0.0001 using cross-validation. Data were converted into spectrogram images for classification with Xception. The highest accuracy, 99.79%, was achieved at epoch 100 with a 0.0001 learning rate. Then, the highest precision occurs when the epoch is 50 with a learning rate of 0.001 and 0.0001, which is 100%. Lastly, Xception performed very well in the ECG image classification. This advantage demonstrates the ability of the model to recognize complex patterns in ECG data more effectively, increasing the reliability of arrhythmia detection. In addition, using DWT as a feature extraction technique allows better signal processing,which contributes to optimal results.
EEG Performance Signal Analysis for Diagnosing Autism Spectrum Disorder using Butterworth and Empirical Mode Decomposition Fathur Rahman, Imam; Melinda, Melinda; Irhamsyah, Muhammad; Yunidar, Yunidar; Nurdin, Yudha; Wong, W.K.; Zakaria, Lailatul Qadri
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 3 (2025): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i3.788

Abstract

Electroencephalography (EEG) is a technique used to measure electrical activity in the brain by placing electrodes on the scalp. EEG plays an essential role in analyzing a variety of neurological conditions, including autism spectrum disorder (ASD). However, in the recording process, EEG signals are often contaminated by noise, hindering further analysis. Therefore, an effective signal processing method is needed to improve the data quality before feature extraction is performed. This study applied the Butterworth Band-Pass Filter (BPF) as a preprocessing method to reduce noise in EEG signals and then used the Empirical Mode Decomposition (EMD) method to extract relevant features. The performance of this method was evaluated using three main parameters, namely Mean Square Error (MSE), Mean Absolute Error (MAE), and Signal-to-Noise Ratio (SNR). The results showed that EMD was able to retain important information in EEG signals better than signals that only passed through the BPF filtration stage. EMD produces lower MAE and MSE values than Butterworth, suggesting that this method is more accurate in maintaining the original shape of the signal. In subject 3, EMD recorded the lowest MAE of 0.622 compared to Butterworth, which reached 20.0, and the MSE value of 0.655 compared to 771.5 for Butterworth. In addition, EMD also produced a higher SNR, with the highest value of 23,208 in subject 5, compared to Butterworth, which reached only 1,568. These results prove that the combination of BPF as a preprocessing method and EMD as a feature extraction method is more effective in maintaining EEG signal quality and improving analysis accuracy compared to the use of the Butterworth Band-Pass Filter alone.
Co-Authors . Roslidar A'yuni, Qurrata Akbar, Muhazir Amalia Amalia Basir, Nurlida Cut Dewi, Cut D Acula, Donata Ega Aulia Sarfina Ernita Dewi Meutia Fahmi Fahmi Farhan Fathur Rahman, Imam Ira Devi Sara Islamy, Fajrul Karlisa Priandana Khairah, Alfita Lailatul Qadri Zakaria Leo, Hendrik Melinda Melinda Miftahujjannah, Rizka Mina Rizky, Muharratul Mirza Rahmat, Muhammad Misbahuddin Misbahuddin Muhammad Reza Syahputra Mulkan Azhary Muttaqin, Ikram Nasaruddin Nasaruddin Pransetia, Arya Handika Putri Mauliza, Putri Putri Rizky Febriani Rafiqi, Ashaf Rini Safitri Rizal Munadi Syahrial Syahrial Syakir, Fakhrus Syukriyadin, Syukriyadin Utama, Muhammad Yoga Wong, W. K Wong, W.K. Yudha Nurdin Yunidar Yuwaldi Away Zulhelmi, Zulhelmi