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All Journal JAIS (Journal of Applied Intelligent System) Journal of Soft Computing Exploration Industrika : Jurnal Ilmiah Teknik Industri Andalasian International Journal of Applied Science, Engineering, and Technology
Pradana, Dio Alif
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Journal of Soft Computing Exploration

 1 
Design of smart baby incubator for low-birth-weight newborns Pradana, Dio Alif; Mukhammad, Yanuar; Suharto, Idola Perdana Sulistyoning; Setiawan, Fachruddin Ari
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.494

Abstract

The newborns mortality rate in Indonesia is still quite high, indicated by the neonatal mortality rate (AKN) of 15 per 1000 Live Births, where the target is only below 10 per 1000 Live Births. This mortality rate can be caused by Low-Birth-Weight (BBLR) cases that leads to death. One form of handling for these cases is using a Baby Incubator for intensive cares, which requires monitoring manually and requires the presence of a nurse around the baby incubator so that the condition of the baby incubator room remains stable. Several studies have been conducted and produced a smart incubator system to address these shortcomings. However, most of the smart incubators only focused on monitoring the condition of the incubator room without observing the condition of the baby inside. Based on this, a study was conducted that focused to producing a smart baby incubator that is capable of real-time monitoring of of room conditions (temperature, humidity, and oxygen levels) and baby conditions (temperature, heart rate, oxygen saturation, baby crying, and baby visuals) by applying the Internet of Things (IoT). The results of this study have the largest number of parameters monitored compared to previous studies.
Development of an IoT-based temperature and humidity prediction system for baby incubators using solar panels Mukromin, Radian Indra; Setiawan, Fachruddin; Pradana, Dio Alif; Hyperastuty, Agoes Santika; Mukhammad, Yanuar
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.497

Abstract

Baby incubators are crucial medical devices to maintain environmental stability for babies born prematurely or have health problems. This research aims to develop a prediction system for temperature and humidity variables in baby incubators by utilizing Internet of Things (IoT) technology and solar panels as the main energy source. Despite advancements in IoT-based incubator systems, existing solutions often rely on reactive approaches, making them less effective in preventing harmful environmental fluctuations. Addressing this gap, this study focuses on optimizing temperature and humidity predictions using artificial intelligence (AI) for proactive control. Using a DHT22 sensor to measure temperature and humidity, as well as a 1 Wp solar panel, the system is designed to operate autonomously in areas with limited access to electricity. The methods used include data collection, data processing to calculate correlation coefficients, and selection of linear regression models for the analysis of relationships between variables. The results showed that the linear regression model applied had a good temperature and humidity prediction with a Mean Squared Error (MSE) value of 0.45 for the training data and 7.32 for the test data.
Implementation of internet of things for leakage current monitoring system in medical equipment Pradana, Dio Alif; Mukhammad, Yanuar; Hyperastuty, Agoes Santika
Journal of Soft Computing Exploration Vol. 6 No. 1 (2025): March 2025
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v6i1.536

Abstract

The rise in electricity consumption, especially in the health sector, has heightened concerns about electrical safety, particularly leakage current in medical equipment. The main objective of this research is to develop an IoT-based leakage current monitoring system specifically designed for low-voltage medical devices, aiming to enhance safety and prevent electrical hazards such as electric shocks and equipment damage. The system used two current sensors module (PZEMT-004T) to measure leakage at points near the voltage source and medical components. Data were processed by a microcontroller and transmitted to a web server for real-time monitoring via mobile devices. Testing on humidifiers and ECGs showed average accuracies of 90.11% and 92.49%, respectively, within a 10 mA range. However, the system could not detect currents below the 3 mA safety threshold because of the sensors reading limitation at 10 mA, indicating a need for sensor improvements. The IoT-based system enhances medical equipment safety, with future work focusing on better sensors and AI for predictive maintenance.
Co-Authors Hyperastuty, A. Santika Hyperastuty, Agoes Santika Inayah, Lailatul Mukromin, Radian Indra Nandang, Iim Puspitasari, Rahma Ajeng Putra, Fadli Dwi Rahma, Naufa Aulia Setiawan, Fachruddin Setiawan, Fachruddin Ari Sulistyoning Suharto, Idola Perdana Widayani, Aisyah winarti, eko Yanuar Mukhammad