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INDONESIA
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
ISSN : -     EISSN : 26568624     DOI : https://doi.org/10.35882/ijeeemi
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics (IJEEEMI) publishes peer-reviewed, original research and review articles in an open-access format. Accepted articles span the full extent of the Electronics, Biomedical, and Medical Informatics. IJEEEMI seeks to be the world’s premier open-access outlet for academic research. As such, unlike traditional journals, IJEEEMI does not limit content due to page budgets or thematic significance. Rather, IJEEEMI evaluates the scientific and research methods of each article for validity and accepts articles solely on the basis of the research. Likewise, by not restricting papers to a narrow discipline, IJEEEMI facilitates the discovery of the connections between papers, whether within or between disciplines. The scope of the IJEEEMI, covers: Electronics: Intelligent Systems, Neural Networks, Machine Learning, Fuzzy Systems, Digital Signal Processing, Image Processing, Electromedical: Biomedical Signal Processing and Control, Artificial intelligence in biomedical imaging, Machine learning and Pattern Recognition in a biomedical signal, Medical Diagnostic Instrumentation, Laboratorium Instrumentation, Medical Calibrator Design. Medical Informatics: Intelligent Biomedical Informatics, Computer-aided medical decision support systems using heuristic, Educational computer-based programs pertaining to medical informatics
Articles 8 Documents
Search results for , issue "Vol. 5 No. 1 (2023): February" : 8 Documents clear
Design of Carbon Dioxide Levels Measurement in Human Expiration Using End Tidal Carbon Dioxide (EtCO2) Capnography Method Fuadi, Rifky Maulana; Yulianto, Endro; Irianto, Bambang Guruh; Mishra , Abhishek
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.160

Abstract

Asthma is a chronic respiratory disease that has become the main reason patients are always rushed to the hospital emergency department. Capnography is a new method for examining asthma by measuring CO2 levels released by the lungs. The aim of this research was to create an EtCO2 capnography device that is able to measure CO2 levels in patients with asthma or difficult breathing to assist doctors in determining the urgency of using a ventilator in a patient. The EtCO2 Capnography device used in the hospital uses a sensor that is expensive, but in this study, a CO2 gas sensor type Cozir-WX-20 was used at a low price. The research was conducted by utilizing a CO2 gas sensor type Cozir-WX-20 which read CO2 concentration in ppm value and a microcontroller as an analog to digital data processor to be displayed on the LCD. Sensor characterization was carried out to compare the side-stream and main-stream methods, response time readings, and the accuracy of the cozir sensor. The resulting data were taken from CO2 cylinders and medical air gas at various flow volume values and was connected to the Cozir sensor, EtCO2 main-stream patient monitors, and side-stream EtCO2 patient monitors. The resulting CO2 readings from CO2 tubes and medical water on the Cozir-WX-20 sensor and main-stream patient monitors obtained an error of 4.6%, namely at a CO2 concentration of 7% or 70,000 ppm and sensor accuracy is above 95%. As for the side-stream method, the reading error is 1.96% and 1.74% at a CO2 concentration of 6-7%. Sensor accuracy on the side-stream method cozir module is above 95%. Response time reading CO2 gas at a concentration of 1%-7% under 5 seconds.
Monitoring the Stability of Oxygen Flow Analyzer on Oxygen Station in the Hospital Rosida, Nur Khabibatul; Rahmawati, Triana; Wisana, I Dewa Gede Hari; Nosike, Maduka
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.161

Abstract

In addition to benefits, oxygen therapy also has certain dangers and side effects. Hence, oxygen therapy must be given at the proper dose by monitoring the patient regularly and adjusting the oxygen flowmeter. The accuracy of flowmeter under standard conditions is guaranteed by manufacturer. Through time and use, the precision may change and the flow accuracy given in a hospital setting may different from the original value. Related to this matter, current research was carried out aiming to conduct further research on oxygen flow analyzer which focused on discussing the accuracy and stability of the oxygen flow sensor against the gold standard. The contribution of this study is to increase the range of oxygen flowrate measurement to 15 liters per minute (LPM). Furthermore, this research used Arduino Mega, while the gas flow sensor used was legris flow sensor. The measurement results were further displayed on TFT LCD equipped with SD Card data storage. The gas flowrate was regulated using a flowmeter (GEA). Meanwhile the comparison tools used Oxygen Analyzer and 1 m3 oxygen gas cylinder. At the testing stage, the sensor reading value on the module that appeared on the TFT LCD was compared with the resultsf a comparison tool with a measurement range of 1 LPM to 15 LPM 6 times at each point. The conclusion from these results is that the calibrator module has a relative error that is still within the allowable tolerance limit of ±10%.
Data Communication Stability Test a Data Acquisition System (DAQ) for Inpatient Rooms Utami, Sentagi Sesotya; Setyonugroho, Winny; Permana, Iman; Lestari, Tri; Taher, Muhammad Dian Saputra; Khanif, Akhmad; Utomo, Gilang Ari Widodo
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.162

Abstract

In inpatient services, the patient's bed is usually limited by a curtain or partition to maintain patient safety. At the time of data collection, obstacles or obstacles were considered as a result of effectiveness and validation of medical device sensor data. This study aims to explain the results of testing the reliability of Bluetooth and internet on CovWatch hardware and applications. This research is an action research; used comparisons using devices (tools) with different specifications. Testing internet and Bluetooth connectivity from the CovWatch unit and applications installed on the Samsung A01, Redmi Note 10 and Oppo A57 devices, the results were mixed. Measurement of the range of connectivity is carried out using a barrier (Selected Semi PVC, Multiplex, Kalsiboard) and without a barrier. The results of this experiment show that the CovWatch Hardware and Samsung A01 are considered the best at obtaining vital sign data, while the Redmi Note 10 and OPPO A57 are not good because some data cannot be obtained so they do not appear on the monitor unit. This test identifies obstructions and optimal distances that can be used to provide data quickly, adopting innovative, flexible and integrated care delivery models to ensure optimal continuity and access.
Analysis of Dialysate pH and Temperature Stability on Hemodialysis Machines Using Internet of Thing Technology P, Noviyanto Putera; Lusiana, Lusiana; Setioningsih, Endang Dian; Luthfiyah, Sari; Pati, Abhilash
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.163

Abstract

Therapy for kidney replacement with hemodialysis is a treatment that is carried out in patients with Chronic Kidney Failure to survive. Related to this matter, this study was done aiming to determine the stability of the dialysate fluid in the hemodialysis machine by measuring the temperature using the DS18B20 sensor and measuring the dialysate pH using the 4502C sensor on pre- and post-hemodialysis. Meanwhile, the research method and the manufacture of this module applied a pre-experimental research design with the independent variables involved are pH value and Dialysate Temperature, while the dependent variables are pH and Temperature Sensor. Furthermore, the control variable is the Traceable Tool. This research made a module using an Esp32 microcontroller system with an LCD that can be monitored using Android via the Internet of Things (IoT) system. In this case, the comparison of the results of the dialysate temperature values ​​during pre and post-obtained the maximum measurement error of 0.2%. Based on the measurement and data analysis, it can be concluded that there was no effect of pH and temperature values ​​during pre and post hemodialysis.
Pressure Sensor Stability Analysis of Positive End Expiratory Pressure Parameters in Flow Analyzer Design Wakidi, Levana Forra; Irianto, Bambang Guruh; Kholiq, Abd.; Prasetyo, Eko Dedi; P, Chandrasekaran
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.164

Abstract

The Positive End Expiratory Pressure (PEEP) parameter is a parameter that must be considered in the process of determining the patient's condition, a safe threshold, and must be in accordance with the settings. However, the PEEP value on the ventilator often does not match the settings so that the measuring instrument capable of detecting PEEP on the ventilator is the Flow Analyzer. The purpose of this study was to design a Flow Analyzer using the MPX2010 sensor to analyze the stability of the PEEP parameters on the ventilator. The main contribution of this research is the design of a simple Flow Analyzer device with stable monitoring of PEEP parameters and the availability of many required setting options. This study used PEEP settings of 0, 5, 8, 11, 14, 17, 20, 23, 26, and 29 cmH2O. In this case, data were collected using a ventilator with VCV (Volume Control Ventilation) and PCV (Pressure Control Ventilation) modes. The tool used for reference from standard measurements was the Standard Flow Analyzer tool. The results of this study indicated that the measurement accuracy of PEEP parameters with the Flow Analyzer module at each PEEP setting had the smallest error of ±0% at 0 cmH2O setting so that it also had the smallest value of 0 by standard. deviation and uncertainty (UA) value 0 at each setting. Meanwhile, the Flow Analyzer measurement module had the largest error in the 5 cmH2O setting, which was ±13.2% with the largest correction value of 0.77. Based on the data obtained, the monitoring of the PEEP parameter was considered quite stable even though the value was still out of tolerance. Therefore, the monitoring of PEEP stability parameters can be implemented during the ventilator calibration process in order to analyze damage and reduce the time of damage to the ventilator.
QRS Detection on Heart Rate Variability Readings using Two Moving Average Methods Rizhky, Ayu Nissa Berlianri; Wisana, I Dewa Gede Hari; Pudji, Andjar; Des, Sima
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.165

Abstract

Heart Rate Variability or the average deviation between heartbeats in humans is influenced by the autonomic nervous system control of heart function. Monitoring HRV is necessary to diagnose the underlying pathophysiology of hypertension, optimize treatment modalities for hypertensive patients with signs of autonomic dysfunction, and predict cardiovascular events in the heart. This study focused on providing an overview of QRS complex detection for heart rate variability or HRV reading using the Two Moving Average method in detecting heart in humans. In addition, current research also determine QRS complex detection for heart rate variability reading by adding a window size feature, then create a QRS Complex detection tool for HRV reading using the Two Moving Average method by adding a window size feature. Furthermore, another aim of this study is to know the FFT signal results in order to see the frequency of each ECG signal generated by the patient. In this study, the use of the Two Moving Average method or moving average makes it easier to find the R peak-to-peak signal, so the heartbeats reading is easier as well. In this study, QRS complex signal detection was performed using lead II pickups using the Two Moving Average method, which was used as a filter or attenuator of unsought signals such as P and T signals in ECG signals. In this case, this method is recommended for detecting patients with high P and T signal values. This was achieved by evaluating and studying each change in window size, an algorithm that uses an equation with two different window widths to generate signal features and detection thresholds, allowing it to adapt to various changes in QRS and noise levels.
Detection of Indonesian Hoax Content about COVID-19 Vaccine using Naive Bayes Multinomial Method Kirana, Annisa Puspa; Prasetyo, Gunawan Budi; Lestari, Ela Widya
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.166

Abstract

One media currently famously used in all worlds is Twitter. The ease of dissemination and the exchange of information is accelerating. Every day, millions of tweets exist using various information, such as politics, technology, sports, academics, and others. The information that is widely found is about COVID-19-19 nowadays. The information on Twitter is not entirely accurate or according to facts and needs to be proven true. Therefore, this study aims to try to detect the information contained in Indonesia using methods of Naive Bayes Multinomial by using the Information Gain feature selection. This research contributes to utilizing data spread on Twitter and social media in detecting hoaxes spread in the community, primarily related to COVID-19 infections. The classification process is carried out by crawling tweets, preprocessing, then using feature selection, namely Information Gain, and classification using the Multinomial Naive Bayes method. Meanwhile, the validation needs in this study use k-fold cross-validation where the existing dataset is divided into training and testing data that will be tested with a confusion matrix. Researchers have carried out the confusion matrix testing process using 720 datasets divided as train data & the test data received an average accuracy value of 81.39%, precision of 80.36%, and recall of 79.73%. The highest accuracy is using k-fold two. The accuracy value reaches 88.8%, the precision value is 79.1%, and the recall value is 86.3%. The lowest accuracy was obtained on the 8th k-fold with an accuracy value of 73.6%, a result precision of 75.4%, and a recall of 86.9%.
IoT-Based Medical Box Improvement for The Elderly Adapting ISO 17025 and Quality of Service Arum, Dewi Sekar; Kurnianto, Danny; Yusro, Muhammad
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 1 (2023): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.167

Abstract

Elderly is a period characterized by limited movement functions in the body. Elderly with multiple comorbidities have a higher risk of non-adherence because receiving more than one type of drug is more susceptible to skipping medication hours so that the elderly need reminders and drug storage areas to maintain drug quality. The main objective of this research is to emerge the robust medical box which gives notification and could be monitored suited to elderly purposes. This research was carried out with Arduino Uno as the control center of the system and using the ESP8266 Wi-Fi module for internet connection. This system uses a DHT-22 sensor, an HW-201 IR sensor and a servo motor. Tool standardization is also carried out through method validation adapting ISO 17025 and network-related Quality of Service (QoS). The results show that the system can work according to the command with an alarm notification on the android application when the clock shows the time to take medicine. Based on the DHT 22 sensor test, by measuring the temperature and humidity, the bias value is 0.318% and the trueness value is 99.7%. This Medical Box tool also has an acceptance limit precision of 83%. Based on the QoS network testing according to THIPON, the network quality is categorized as very good for throughput of 5241 Kbps, packet loss of 0%, delay of 136.5 msec, and jitter of 21.28 which are categorized as very good. This study designed a system to make it easier for the elderly as a reminder of the schedule for taking medication as well as a place to store drugs that can maintain the quality of drugs.

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