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INDONESIA
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Published by Polilteknik Kesehatan Kemenkes Surabaya
ISSN : -     EISSN : 26568624     DOI : https://doi.org/10.35882/ijeeemi
Core Subject : Health, Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Health Professions Materials Science & Nanotechnology
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
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 6 Documents
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Search results for , issue "Vol. 3 No. 1 (2021): February" : 6 Documents clear
Design an Occlusion Calibrator using XGZP6887 and Servo Motor MG966R as a Simulator Auliya, Rizki; Syaifudin, Syaifudin; Soetjiatie, Liliek
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 1 (2021): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i1.193

Abstract

A foreign fluid that enters the patient can cause some bodily reactions including infection, air embolism and blood clot. Side effects given will be fatal to the body, one of which occurs the blockage of the capillary vessels in the heart that can cause heart attack to stroke. The purpose of this research is to design a tool that can be used to measure maximum pressure as a form of the calibration of the syringe pump and infusion pump. The contribution of this research is that the system can simulate the presence of blockages in fluid flow and detect large pressure values detected by the Under Test Unit (UUT) with a motor peer round system that opens/closes fluid flow. Servo Motor MG966R simulate the presence of blockage with constant motor degree until the alarm UUT reads, then Sensor XGZP6887 detects the pressure generated by the blockage and processed by the microcontroller and displayed on the LCD display of the character. This study resulted in a maximum pressure average value of 7.12 Psi. The results showed that data retrieval had an error value of -0.12. This research can be implemented to perform pressure measurements on the syringe pump or infusion pump.
Development of a Low-Cost and Efficient ECG devices with IIR Digital Filter Design Wisana, I Dewa Gede Hari; Nugraha, Priyambada Cahya; Rachman, Rizki Aulia
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 1 (2021): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i1.194

Abstract

Measurement of biosignals such as electrocardiograph has the interpretation of noise from other signals. The noise can interfere with the measurement of the heart signal and make the measurement inaccurate, so the purpose of this study is to make a 6-Lead Electrocardiogram module with an Arduino-Based Digital Filter. By using a digital filter. The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino which has been applied digital filters with Frequency with 0.5Hz – 100Hz cut-off. The instrument is compared with a factory electrocardiograph. Filter measurements using 460 input data. Butterworth filter with the greatest emphasis on order 8 frequency 0.5Hz produces an emphasis of -5.74298158 dB and a frequency of 100Hz produces an emphasis of -5.93529424 dB. The Chebyshev I filter has the greatest emphasis on order 6 frequency 0.5Hz producing an emphasis of -3.27104076 dB and on order 8 frequency 100Hz producing an emphasis of -5.08730424 dB. Chebyshev II filter the biggest emphasis on the order of frequency 0.5Hz produces a suppression of -44,66011104 dB and 80Hz frequency produces a suppression of -37,3653957 dB. Elliptic filters the greatest emphasis on order 6 frequency 0.5Hz produces an emphasis on -1.55429354 dB and 100Hz frequency on order 8 produces an emphasis on -2.2849115 dB. The results of this study can be implemented on a 6-Lead ECG module to eliminate noise or interference when tapping ECG signals.
Communication Coroutines For Parallel Program Using DW26010 Many Core Processor Singh, Ajit
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 1 (2021): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i1.195

Abstract

Communication between parallel programs is an indispensable part of parallel computing. SW26010 is a heterogeneous many-core processor used to build the Sunway Taihu Light supercomputer, which is well suited for parallel computing. There is the designing and implementing a coroutine scheduling system on the SW26010 processor to improve its concurrency, it is very important and necessary to achieve communication between coroutines for the coroutine scheduling system in advance. Therefore, this paper proposes a communication system for data and information exchange between coroutines on SW26010 processor, which contains the following parts. The designing and implementation a producer-consumer mode channel communication based on ring buffer, and it designs synchronization mechanism for condition of multi-producer and multi-consumer based on the different atomic operation on MPE (management processing element) and CPE (computing processing element) of SW26010. There is also the designing of a wake-up mechanism between the producer and the consumer, which reduces the waiting of the program for communication. The testing and analysis of the performance of channel in different numbers of producers and consumers, draw the conclusion that when the number of producers and consumers increases, the channel performance will decrease
Support Vector Machine And K-Nearest Neighbor Based Liver Disease Classification Model Assegie, Tsehay Admassu
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 1 (2021): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i1.196

Abstract

Machine-learning approaches have become greatly applicable in disease diagnosis and prediction process. This is because of the accuracy and better precision of the machine learning models in disease prediction. However, different machine learning models have different accuracy and precision on disease prediction. Selecting the better model that would result in better disease prediction accuracy and precision is an open research problem. In this study, we have proposed machine learning model for liver disease prediction using Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) learning algorithms and we have evaluated the accuracy and precision of the models on liver disease prediction using the Indian liver disease data repository. The analysis of result showed 82.90% accuracy for SVM and 72.64% accuracy for the KNN algorithm. Based on the accuracy score of SVM and KNN on experimental test results, the SVM is better in performance on the liver disease prediction than the KNN algorithm
Design of Vital Sign Monitor with ECG, BPM, and Respiration Rate Parameters Oka, Gede Aditya Mahendra; Pudji, Andjar; Mak’ruf, Muhammad Ridha
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 1 (2021): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i1.197

Abstract

Vital sign monitor is a device used to monitor a patient's vital sign, in the form of a heartbeat, pulse, blood pressure, temperature of the heart's pulse form continuously. Condition monitoring in patients is needed so that paramedics know the development of the condition of inpatients who are experiencing a critical period. Electrocardiogram (ECG) is a physiological signal produced by the electrical activity of the heart. Recording heart activity can be used to analyze how the characteristics of the heart. By obtaining respiration from outpatient electrocardiography, which is increasingly being used clinically to practice to detect and characterize the abnormal occurrence of heart electrical behavior during normal daily activities. The purpose of this study is to determine that the value of the Repiration Rate is taken from ECG signals because of its solidity. At the peak of the R ECG it has several respiratory signals such as signals in fluctuations. An ECG can be used to determine breathing numbers. This module utilizes leads ECG signals to 1 lead, namely lead 2, respiration rate taken from the ECG, BPM in humans displayed on a TFT LCD. This research module utilizes the use of filters to obtain ECG signals, and respiration rates to display the results on a TFT LCD. This module has the highest error value of 0.01% compared to the Phantom EKG tool. So this module can be used for the diagnosis process
Novel Coronavirus Pandemic in Indonesia: Cases Overview and Daily Data Time Series using Naïve Forecast Method Kirana, Annisa Puspa; Bhawiyuga, Adhitya
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 3 No. 1 (2021): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v3i1.198

Abstract

At the end of December 2019, the virus emerges from Wuhan, China, and resulted in a severe outbreak in many cities in China and expanding globally, including Indonesia. Indonesia is the fourth most populated country globally. As of February 2021, Indonesia in the first rank of positive cases of COVID-19 in Southeast Asia, number 4 in Asia, and number 19 in the world. Our paper aims to provide detailed reporting and analysis of the COVID-19 case overview and forecasting that have hit Indonesia. Our time-series dataset from March 2020 to January 2021. Summary of cases studied included the number of positive cases and deaths due to COVID-19 on a daily or monthly basis. We use time series and forecasting analysis using the Naïve Forecast method. Naïve forecast is one of the simplest forecasting methods, and it is very useful to be considered as a benchmark method for comparing models. The prediction is daily case prediction for six months starting from February 1, 2021, to June 30, 2021, using active cases daily COVID-19 data in all provinces in Indonesia. The highest monthly average case prediction is in June, which is 35,662 cases. Our COVID-19 prediction study has a mean absolute percentage error (MAPE) score of 15.85%.

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