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All Journal Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Nasional Aplikasi Mekatronika, Otomasi dan Robot Industri (AMORI) Sewagati
Nugroho, Dwi Oktavianto Wahyu
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Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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Sistem Monitoring dan Kontrol Otomatis Terintegrasi IoT pada Vertical Crab House untuk Meningkatkan Potensi Hidup Kepiting Bakau di PT. Crab Crab Aquatic Mujiyanti, Safira Firdaus; Raditya, Murry; Nugroho, Dwi Oktavianto Wahyu; Darwito, Purwadi Agus; Septyaningrum, Erna; Zein, Muhammad Ikhsanuddin; Lokeswara, Rajendra; Rishwanda, Muhammad Akmal; Darmawan, Tiffany Rachmania; Rohid, Abdul; Nanta, Tepy Lindia
Sewagati Vol 8 No 3 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i3.914

Abstract

Budidaya kepiting bakau dengan Vertical Crab House menjadi alternatif pembesaran kepiting dengan lahan terbatas untuk memenuhi permintaan di perkotaan. Namun masih banyak resiko kematian kepiting bakau disebabkan proses pengendalian kualitas air masih manual dalam mengendalikan kualitas air sirkulasi. Hal ini membutuhkan tenaga manusia dan waktu ekstra untuk memastikan kualitas air sirkulasi sesuai dengan kondisi lingkungan pertumbuhan kepiting bakau. Ditambah lagi metode Vertical Crab House tidak dapat mengidentifikasi kondisi kualitas air secara tepat, tidak dapat mengecek kondisi kualitas air secara real-time, dan tidak dapat mengecek kondisi temperatur, salinitas, amonia, dan pH secara simultan. Kondisi lingkungan yang tidak sesuai dengan parameter dan tidak termonitor membuat resiko kematian kepiting bakau masih sangat tinggi sehingga menyebabkan pembudidaya mengalami kerugian yang cukup besar. Permasalahan tersebut menjadi dasar terciptanya sistem otomatisasi pengendalian kualitas air untuk mengoptimalkan proses budidaya kepiting bakau dengan metode Vertical Crab House. Proses pengendalian kualitas air tersebut dilakukan dengan memasang sensor, kontroler, dan aktuator yang diintegrasikan sehingga proses pengendalian kualitas air dapat berjalan terus-menerus untuk memastikan air yang tersirkulasi sesuai dengan lingkungan yang optimal bagi pertumbuhan kepiting bakau. Selain itu, kualitas air sirkulasi pada budidaya dapat dipantau secara real-time melalui aplikasi smartphone.
The external controller solutions (ECS) based on programmable logic controller with humanmachine interface: A case study for the water level simulator plant Patrialova, Sefi Novendra; Winata, Waga; Mujiyanti, Safira Firdaus; Adziima, Ahmad Fauzan; Nugroho, Dwi Oktavianto Wahyu
Jurnal Nasional Aplikasi Mekatronika, Otomasi dan Robot Industri (AMORI) Vol 3, No 2 (2024): December
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213560.v3i2.21918

Abstract

The External Controller Solutions (ECS) is designed with the flexibility and able to be integrated with various plants. The ECS has been built using PLC and HMI.  Several tests have been carried out in developing this ECS, including testing Digital Input/Output (DI/DO) and Analog Input/Output (AI/AO) voltages. This ECS be able to control up-to 8 devices simultaneously with the data refresh time interval of 100 ms and be able to handle up-to 10,000 operating cycles within 24 hours without significant performance degradation. ECS performance is very good, proven by the results showing that the system runs well within 20-35 °C of temperatures range and 20%-80% of humidity. To show the advantage of ECS, it has already been integrated on the Water Level Simulator (WLS) plant and successfully controlled the flow through the VSD at 54 RPM/Hz in range of 15-30 Hz.
A Mattress-Integrated ECG System for Home Detection of Obstructive Sleep Apnea Through HRV Analysis Using Wavelet Transform and XGBoost Classification Fitrieyatul Hikmah, Nada; Setiawan, Rachmad; Amalia, Rima; Syulthoni, Zain Budi; Nugroho, Dwi Oktavianto Wahyu; Syakir, Mu’afa Ali
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 4 (2025): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i4.1022

Abstract

Obstructive Sleep Apnea (OSA) is a potentially life-threatening sleep disorder that often remains undiagnosed due to the complexity of conventional diagnostic methods such as polysomnography (PSG). Currently, there is a lack of accessible, non-invasive diagnostic solutions suitable for home use. This study proposes a novel approach to automate OSA detection using single-lead electrocardiogram (ECG) signals acquired through non-contact conductive fabric electrodes embedded in a mattress, enabling unobtrusive monitoring during sleep. The main contributions of the proposed study are a mattress-embedded contactless ECG monitoring system eliminating the discomfort of traditional electrodes, and an advanced signal processing framework integrating wavelet decomposition with machine learning for precise OSA identification. ECG signals from 35 subjects (30 male, 5 females, aged 27-63 years) diagnosed with OSA were obtained from the PhysioNet Apnea-ECG database, originally sampled at 100 Hz and up-sampled to 250 Hz for consistency with experimental recordings from healthy volunteers tested in various sleep positions. Signals were recorded non-invasively during sleep in various body positions and processed using the Discrete Wavelet Transform (DWT) up to the third level of decomposition. The processing of ECG signals involved Heart Rate Variability (HRV) analysis, which was applied to extract information in the time domain, frequency domain, and non-linear properties. By analyzing HRV on the respiratory sinus arrhythmia spectrum, the respiration signal was obtained from ECG-derived respiration (EDR). Feature selection was performed using ANOVA, resulting in a set of key features including respiratory rate, SD2, SDNN, LF/HF ratio, and pNN50. These features were classified using the XGBoost algorithm to determine the presence of OSA. The proposed system achieved a detection accuracy of 96.7%, demonstrating its potential for reliable home-based OSA diagnosis. This method improves comfort through non-contact sensing and supports early intervention by delivering timely alerts for high-risk patients
Co-Authors Adziima, Ahmad Fauzan Amalia, Rima Darmawan, Tiffany Rachmania Fitrieyatul Hikmah, Nada Lokeswara, Rajendra Mujiyanti, Safira Firdaus Nanta, Tepy Lindia Patrialova, Sefi Novendra Purwadi Agus Darwito Raditya, Murry Rishwanda, Muhammad Akmal Rohid, Abdul Septyaningrum, Erna Setiawan, Rachmad Syakir, Mu’afa Ali Syulthoni, Zain Budi Winata, Waga Zein, Muhammad Ikhsanuddin