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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknokes Indonesian Journal of electronics, electromedical engineering, and medical informatics Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science International Journal of Advanced Health Science and Technology Gemakes: Jurnal Pengabdian Kepada Masyarakat Frontiers in Community Service and Empowerment Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknokes
Triwiyanto Triwiyanto
Poltekkes Kemenkes Surabaya
Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Nursing Public Health Other

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Noise Reduction of Motion and EMG Artifacts in Holter ECG Using IIR Filters for Robust Arrhythmia Detection Sumber Sumber; Endang Dian S; Triwiyanto Triwiyanto; Roichatun Nashichah; Vijay Anant Athavale
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 2 (2026): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i2.9426

Abstract

Ambulatory Holter electrocardiography (ECG) enables continuous monitoring for detecting transient arrhythmias; however, its diagnostic reliability is significantly degraded by motion artifacts and electromyographic (EMG) interference. Under severe motion artifact conditions, prior studies report that ambulatory ECG SNR can fall below −10 dB , although SNR levels vary substantially depending on activity type and electrode placement, reducing usable data segments and impairing arrhythmia detection. While advanced denoising methods such as wavelet transforms and deep learning achieve high accuracy, their computational complexity limits real-time deployment in resource-constrained embedded systems. This reveals a critical gap in lightweight methods that jointly optimize noise suppression, morphological preservation, and downstream diagnostic performance. This study proposes a computationally efficient IIR Butterworth bandpass filtering framework for real-time IoT-based Holter ECG systems. The system combines three-lead ECG acquisition, embedded processing on an ESP32, and real-time visualization. Performance is assessed using SNR, mean squared error (MSE), Pearson correlation, and confusion matrix-based detection metrics on ten male participants under controlled motion and muscle artifact conditions. Results demonstrate statistically significant SNR improvements for motion artifacts (ΔSNR = 9.47 ± 1.96 dB, t(9) = 15.28, p < 0.001) and EMG artifacts (ΔSNR = 16.73 ± 0.91 dB, t(9) = 58.11, p < 0.0001). Post-filtering morphological fidelity was high, with mean Pearson correlation of 0.963 for motion artifacts and 0.945 for muscle artifacts. These signal quality improvements translated into 95.3% post-filtering arrhythmia detection accuracy (sensitivity: ≈96.0%, specificity: ≥97.0%, F1-score: ≥95.0%), significantly exceeding the 70% minimum performance threshold adopted in this study as a conservative screening criterion (t(9) = 29.7, p < 0.001). Despite dataset limitations (n = 10), the proposed framework provides an effective trade-off between computational efficiency and diagnostic reliability, supporting scalable and real-time ambulatory ECG monitoring for early arrhythmia screening.
Android-Assisted Cardiovascular Education and Risk Screening to Improve Coronary Heart Disease Literacy in Primary Care: A One-Group Pre–Post Community Intervention in Indonesia Sari Luthfiyah; Triwiyanto Triwiyanto; Syevana Dita Musvika; Yudha Aditya Fahriza; Alfred Rafu Neno; Rizky Dwi Sisantiara
Frontiers in Community Service and Empowerment Vol. 5 No. 2 (2026): June
Publisher : Forum Ilmiah Teknologi dan Ilmu Kesehatan (FORITIKES)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ficse.v5i2.145

Abstract

Coronary heart disease (CHD) prevention in primary care is constrained by limited consultation time, uneven health literacy, and insufficient reinforcement after one-off education. This community service program evaluated a hybrid intervention combining clinician-led education, guided Android application use, and self-risk screening. The program was delivered at Candi Primary Health Center, Sidoarjo, Indonesia, on 9 June 2026 using a one-group pre-test–post-test design. Community members were recruited consecutively; paired analysis included participants who attended the intervention and completed matchable pre- and post-tests. The intervention comprised baseline assessment, structured CHD education, application demonstration, hands-on practice, and immediate post-test. Knowledge was assessed with an expert-reviewed 20-item true–false questionnaire scored from 0 to 100. Approximately 60 electronic entries were screened; after duplicate and incomplete records were removed, 13 valid paired observations remained. The mean knowledge score changed from 63.50 ± 12.05 (pre-test) to 97.00 ± 4.62 (post-test), with an absolute change of 33.50 points (95% CI: 30.09–36.91), p < 0.001, and a large effect size (Cohen’s dz = 2.54). Application access, screening completion, and assistance needs were 54 (90%), 60 (100%), and not formally assessed in the dataset, respectively. The hybrid intervention was feasible under supervised conditions and was associated with an immediate improvement in CHD literacy. However, the small uncontrolled sample, immediate outcome assessment, and absence of longitudinal usage data preclude conclusions about sustained behavior change. Integration into routine non-communicable disease education should be accompanied by cadre training, user support, and longer-term evaluation.
Improving the Digital Marketing Capacity of MSME Actors through Practice-Based Marketplace Training in Balongdowo Village, Sidoarjo, Indonesia Triwiyanto Triwiyanto; Sari Luthfiyah; Bedjo MKes; Fairooz Azzahra Darmawan; Hafizh Ammar Wahyudi
Frontiers in Community Service and Empowerment Vol. 5 No. 2 (2026): June
Publisher : Forum Ilmiah Teknologi dan Ilmu Kesehatan (FORITIKES)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ficse.v5i2.146

Abstract

Digital marketing support for micro-, small-, and medium-sized enterprises (MSMEs) is often delivered as uniform training, even though participants differ substantially in their baseline capabilities. This community-based program evaluation mapped the digital readiness of MSME actors in Balongdowo Village, Sidoarjo, Indonesia, and translated the findings into a staged marketplace-assistance strategy. The study was embedded in the 2026 Community Partnership Program entitled “Optimalisasi Transformasi Digital UMKM di Desa Balongdowo: Peningkatan Kapasitas, Inovasi Produk, dan Akses Pasar,” implemented by Poltekkes Kemenkes Surabaya with the Balongdowo Village Government from May to October 2026. The core seminar and marketplace workshop was held on 10 June 2026 and included registration and baseline assessment, practical digital-marketing instruction, marketplace demonstration, hands-on product-content practice, discussion, post-test administration, and follow-up mentoring. Anonymized baseline participant records were analyzed descriptively using frequencies, percentages, and measures of central tendency and dispersion. Thirty-three participants were included. Their mean age was 38.8 years (SD 10.9; range 24-60), 63.6% were women, and 63.6% operated food businesses. Monthly business income was below IDR 2 million for 90.9% of participants. Although 45.5% reported operating an online business, only 36.4% had a commercial account or platform presence; 18.2% used Shopee, 9.1% used TikTok, and 9.1% reported an affiliate-oriented account. Only 18.2% reported business or platform affiliation. The findings demonstrate progressive attrition from online presence to platform formalization and network embeddedness. A presence-platform-network continuum is therefore proposed to tailor assistance: foundational account creation and digital safety for non-users, structured storefront and transaction-management support for informal online sellers, and content, promotion, affiliate, and peer-mentor strategies for platform-active participants. Because participant-linked pre-post scores and longitudinal platform outcomes were not available, no claim of training effectiveness is made
Effectiveness of Bluetooth communication of digital stethoscope using quality of service method Endang Dian Setyoningsih; Sumber Sumber; Triwiyanto Triwiyanto; Farid Amrinsani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.25882

Abstract

This study aims to design and evaluate a wireless electronic stethoscope that can transmit heart sound using Bluetooth HC-05 and Bluetooth 5.0 transmitter. This novel design contributes to the remote diagnosis and monitoring of heart conditions, especially for patients with infectious diseases. The heart sound signals are captured using a mic condenser mic, amplified, filtered, and converted to digital data by a microcontroller. The data are then transmitted by Bluetooth HC-05 to a module and by Bluetooth 5.0 transmitter to a headset. The quality-of-service parameters such as throughput, delay, and packet loss ratio (PLR) of the data transmission at different distances are measured. The results show that the wireless electronic stethoscope can transmit heart sound data with a small PLR of 0.10% and a throughput of 1002.5 bps. The study concludes that the wireless electronic stethoscope is an effective and useful device for examining heart conditions remotely, without compromising the functionality of the device
Low-cost and open-source anthropomorphic prosthetics hand using linear actuators Triwiyanto Triwiyanto; I Putu Alit Pawana; Torib Hamzah; Sari Luthfiyah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14799

Abstract

A robust, low cost, open-source, and low power consumption in the research of prosthetics hand is essential. The purpose of this study is to develop a low-cost, open-source anthropomorphic prosthetics hand using linear actuator based on electromyography (EMG) signal control. The main advantages of this proposed method are the low-cost, lightweight and simplicity of controlling the prosthetic hand using only single channel. This is achieved by evaluating the DC motor and exploring number of locations of the EMG signal. The development of prosthetics hand consists of 3D anthropomorphic hand design, active electrodes, microcontroller, and linear actuator. The active electrodes recorded the EMG signal from extensor carpi radialis longus. The built-in EMG amplifier on the electrode amplified the EMG signal. Further, the A/D converter in the Arduino microcontroller converted the analog signal into digital. A filtering process consisted of bandpass and notch filter was performed before it used as a control signal. The linear actuator controlled each finger for flexion and extension motion. In the assessment of the design, the prosthetic hand capable of grasping ten objects. In this study, the cost and weight of the prosthetics hand are 471.99 US$ and 0.531 kg, respectively. This study has demonstrated the design of low cost and open-source of prosthetics hand with reasonable cost and lightweight. Furthermore, this development could be applied to amputee subjects.
Evaluating the effectiveness of digital filtering techniques in electronic stethoscopes: a study of Kalman and Butterworth filters Endang Dian Setioningsih; Sumber Sumber; Triwiyanto Triwiyanto; Vugar Abdullayev; Farid Amrinsani; Bima Maulana Raharjo; Tetrik Fa’altin
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.8674

Abstract

Heart sound, or phonocardiogram (PCG), signals are often distorted by noise from respiration, movement, and the surrounding environment, which complicates accurate cardiac feature extraction in portable monitoring systems. This study aims to design and evaluate an effective digital filtering method to enhance PCG signal quality obtained from a low-cost acquisition system based on a condenser microphone sensor and an ESP32 microcontroller. The main contribution of this work is the implementation and comparison of two noise-reduction approaches: Butterworth band-pass filters of various orders and the Kalman filter applied to PCG signals acquired from mannequin-based simulations. Data were recorded for 10 seconds at a 1000 Hz sampling rate, processed in MATLAB, and analyzed using the fast Fourier transform (FFT) to determine the optimal frequency ranges. Experimental results demonstrate that the 8th-order Butterworth band-pass filter achieved the highest signal-to-noise ratio (SNR) improvement, averaging 25.659 dB, outperforming other configurations. These findings indicate that an appropriately tuned Butterworth filter provides a simpler yet robust solution for real-time PCG denoising in embedded systems. Future work will integrate the filtering process directly into the ESP32 firmware and evaluate its performance on human subjects to enhance clinical applicability.
SOSIALISASI LAYANAN WEBGIS UNTUK MENINGKATKAN PELAYANAN POSYANDU DI DESA BALONGDOWO: SOCIALIZATION OF WEBGIS SERVICES TO IMPROVE POSYANDU SERVICES IN BALONGDOWO VILLAGE Bedjo Utomo; Triwiyanto Triwiyanto; Sari Luthfiyah; Dewi Sari Oswarida
GEMAKES: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2026): GEMAKES: Jurnal Pengabdian Kepada Masyarakat
Publisher : Politeknik Kesehatan Kemenkes RI Jakarta I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36082/gemakes.v6i1.2679

Abstract

Informasi yang akurat dan terkini memegang peran penting dalam pengelolaan data, oleh karena itu, ketersediaan Sistem Informasi berbasis wilayah (WebGIS) menjadi solusi yang sangat dibutuhkan untuk mendukung analisis, pemetaan, dan pengambilan keputusan. Tujuan pengabdian ini adalah memberikan sosialisasi pada pengelola kesehatan tentang pemanfaatan sistim informasi pemetaan berbasis WebGiS. Pengabdian ini menggunakan metode mini workshop, dimana yang menjadi responden adalah bidan desa, kader kesehatan dan pamong desa. Pengabdian ini menggunakan software Quantum GiS yang sudah diaplikasi menggunakan data wilayah desa Balongdowo. Sebelum pelaksanaan kegiatan dilakukan Forum group discusi untuk menetapkan masalah terkait penyebaran penduduk, luas wilayah sehingga penggunaan aplikasi WeGis dapat menjadi solusi untuk mengevaluasi program kesehatan. Hasil pengabdian menunjukkan bahwa aplikasi Quantum Gis berbasis Web mampu meningkatkan efektivitas pemetaan wilayah posyandu di Desa Balongdowo. Manfaat dari pengabdian  ini, adalah secara khusus bagi pengelola program untuk meningkatkan pelayanan kesehatan, dan juga untuk memotivasi masyarakat untuk mengembangkan WebGis khususnya dalam mengelola resiko terjadinya rawan gizi.
Embedded Machine Learning on ESP32 for Upper-Limb Exoskeletons Based on EMG Triwiyanto Triwiyanto; Anita Miftahul Maghfiroh; Levana Forra Wakidi; Syevana Dita Musvika; Bedjo Utomo; Sumber Sumber; Priyambada Cahya Nugraha; Wahyu Caesarendra
Jurnal Teknokes Vol. 18 No. 4 (2025): Desember
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jteknokes.v18i4.134

Abstract

Stroke remains one of the primary causes of long-term disability worldwide and frequently results in persistent impairment of upper limb motor function. To support more effective and intensive rehabilitation, there is a need for wearable devices that can interpret muscle activity and autonomously assist limb movement without relying on an external computer. This study aims to design and implement an upper-limb rehabilitation exoskeleton that is driven by electromyography (EMG) signal classification using machine learning and by real-time elbow angle monitoring, with all models deployed directly on an ESP32 microcontroller. The proposed exoskeleton is built from lightweight, ergonomic 3D-printed components and operates in both unilateral and bilateral modes. Its main contributions include: (1) embedding real-time EMG classification models on the ESP32 so that the device can function independently, (2) integrating EMG-based motor control with elbow angle feedback from an MPU6050 inertial measurement unit, and (3) incorporating a load cell to estimate biceps force during training. EMG signals from the forearm flexor muscles are processed to extract statistical features such as variance (VAR), waveform length (WL), integrated EMG (IEMG), and root mean square (RMS). These features are used to train Random Forest, Decision Tree, Support Vector Machine (SVM), and XGBoost classifiers. The trained models are converted to C code using the micromlgen library for execution on the ESP32. System evaluation involved thirty male participants aged 20–25 years with body weights between 50–85 kg. All tested models achieved 100% accuracy in distinguishing relaxed versus grasping muscle contractions, while the correlation of elbow angles between unilateral and bilateral ESP32 systems reached 0.9469, indicating highly consistent motion detection. The Decision Tree model was selected for deployment due to its superior memory efficiency on the microcontroller. These results demonstrate that the developed ESP32-based exoskeleton provides a practical, efficient, and easily integrable solution for wearable stroke rehabilitation
Development process of decision support systems using data mining technology Bahar Asgarova; Elvin Jafarov; Nicat Babayev; Allahshukur Ahmadzada; Vugar Abdullayev; Triwiyanto Triwiyanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp703-714

Abstract

Decision support systems (DSS) play a pivotal role as computerized tools, guiding and enhancing decision-making processes vital for organizational progress. This research focuses on developing a system tailored for dynamic decision-making, particularly emphasizing the integration of data mining technology. Decision algorithms and neural networks are discussed in depth, providing a comprehensive understanding of the analytical tools crucial for effective decision support. Additionally, the research sheds light on potential risks, ensuring a nuanced view of challenges that may impact the development of DSS. A significant portion of the study is dedicated to the design of DSS architecture and the strategic integration of data mining within the database. The proposed development stages for a business information system, ranging from feasibility study to release, serve as a structured framework for practical implementation. Details within each stage, including data analysis, cleaning, and module development, are meticulously examined. Emphasis is placed on critical steps such as system design, database design, and extract, transform, load (ETL) process design, elucidating their importance in the holistic development of DSS. The conclusion reinforces the paramount importance of leveraging data mining technology in the process of developing decision support systems.
Co-Authors A K M Bellal Hossain Abhilash Pati Achmad Rizal Achmad Rizal Alfred Rafu Neno Alfrinscha Dinda Larasati Allahshukur Ahmadzada Amrinsani, Farid Andi Fathkur Rohman Andjar Pudji Andjar Pundji ANGELA ROSARI Anita Miftahul Maghfiroh Arifah Putri Caesaria Bahaa Eddine ELBAGHAZAOUI Bahar Asgarova Bambang Guruh Irianto Bedjo MKes Bima Maulana Raharjo Cantika Melinda Chandrika, G.Naga Dewi Sari Oswarida Dwi Herry Andayani Dyah Titisari, Dyah Elvin Jafarov Endro Yulianto Faheem Ahmad Reegu Fairooz Azzahra Darmawan Forra Wakidi, Levana Gita Aprilyana Hafizh Ammar Wahyudi Hidayanti, Nuril I Dewa Gede Hari Wisana Indrato, Tri Bowo jusuf julianto Karpagam, J. Kinanti Elok Putri Lamidi, Lamidi Liliek Soetjiatie Lintang Ayu Pramesti Lusiana Lusiana Luthfiyah, Sari M Shaib Moch Sahrul Triandi Putra Sahrul Muhammad Fauzi Muhammad Ridha Mak'ruf Musyahadah Arum Pertiwi Nicat Babayev Nindia Rena Saputri Nuril Hidayanti Pawana, I Putu Alit Phuoc-Hai Huynh Priyambada Cahya Nugraha Raden Duta Ikrar Abadi Richard, Titus Rizky Dwi Sisantiara Roichatun Nashichah Sandeep Kumar Gupta Sari Lutfiyah Sasivimon Sukaphat Setioningsih, Endang Dian Shadrach, Finney Daniel Shofiyah Shofiyah Silvian, Fawaida Sumber, Sumber Syarifatul Ainiyah Syevana Dita Musvika Tetrik Fa’altin Torib Hamzah Torib Hamzah Triana Rahmawati Utomo, Bedjo Vijay Anant Athavale Vijay Anant Athavale Vishwajeet Shankhwar Vugar Abdullayev Vugar Abdullayev Vugar Abudlayev Wahyu Caesarendra Wahyu Caesarendra Wahyu Caesarendra Yudha Aditya Fahriza