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Department of Electromedical Engineering, Poltekkes Kemenkes Surabaya Jl. Pucang Jajar Timur No. 10, Surabaya, Indonesia
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Journal of Electronics, Electromedical Engineering, and Medical Informatics
Published by Polilteknik Kesehatan Kemenkes Surabaya
ISSN : -     EISSN : 26568632     DOI : https://doi.org/10.35882/jeeemi
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
The Journal of Electronics, Electromedical Engineering, and Medical Informatics (JEEEMI) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics which covers three (3) majors areas of research that includes 1) Electronics, 2) Biomedical Engineering, and 3)Medical Informatics (emphasize on hardware and software design). Submitted papers must be written in English for an initial review stage by editors and further review process by a minimum of two reviewers.
Arjuna Subject : Teknik (semua kategori) - Teknik Biomedis
Articles 6 Documents
 1 
Search results for , issue "Vol 4 No 1 (2022): January" : 6 Documents clear
Analysis Of Baby Incubator Humidity Based PID with Kangaroo Mode Singgih Yudha Setiawan; Dwi Herry Andayani; Andjar Pudji; Liliek Soetjiatie; Alievya Brillianty Anugrah Kusuma
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.6

Abstract

The main factor that affects the parameters of the workings of humidity in the baby incubator is the sensor used to read the humidity in the room. The purpose of this study is to analyze the humidity sensor in the baby incubator using 2 humidity sensors (DHT11 and DHT22) in the different location. The manufacture of this device used an after-only design, with a comparison device of INCU Analyzer, DHT11, and DHT22 sensors. Based on the measurement, DHT11 produced a value of 46%, while DHT22 produced a value of 55.45% with BPFK standards of 50%-70%. Based on the results of measurements using the INCU Analyzer, the average error value for DHT11 is 16.05%, while DHT22 is 3.47%. Therefore, the results showed that the DHT22 sensor was more accurate to be used in baby incubators because the measurement results were under BPFK standards and produced a low error value. This can be further implemented in a baby incubator making to improve the health and safety of the babies
Analysis of the Drop Sensors Accuracy in Central Peristaltic Infusion Monitoring Displayed on PC Based Wireless (TCRT5000 Drop Sensor) Hanna Firdaus; Bambang Guruh Irianto; Sumber; Jing Lu
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.5

Abstract

In some hospitals the infusion is still done manually, medical staff observes fluid drip directly and then controls its rate using a mechanical resistor (clamp), this method is certainly far from the level of accuracy. Infusion pump is a medical aid that has functions to control and ensure the correct dose of infusion fluid that is given to patients under treatment. The purpose of this study is to analyze the accuracy of the TCRT5000 as a drop sensor, based on readings of the infusion pump monitoring system. This module consists of a TCRT5000 drop sensor module, comparator circuit, monostable circuit, stepper motor, L298N motor driver, and ATmega328 microcontroller. The droplets are detected by the TCRT 5000 sensor, then amplified by a comparator and monostable circuit, then the flow rate and remaining volume readings are generated by the ATmega328 microcontroller. Furthermore, this data is sent to the Personal Computer (PC) via wireless HC-11. The results of the flow rate module measurement show that the highest error value is 4% at the 30 ml/hour setting, and the lowest error value is 1% at the 60 ml/hour setting. While the results of the flow rate measurement using an Infuse Device Analyzer, the highest error value is 2,2% at the 30 ml/hour setting, and the lowest error value is 0,58% at the 100 ml/hour setting. This infusion pump monitoring is designed centrally to facilitate the nurse's task in monitoring the infusion dose accurately that is given to the patient.
The Effect of Inlet Notch Variations in Pico-hydro Power Plants with Experimental Methods to Obtain Optimal Turbine Speed Naufal Praska Zakariz; Anggara Trisna Nugraha; Khongdet Phasinam
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.4

Abstract

ABSTRACT Energy is an important element in the continuity of human activities. Indonesia has the potential to produce 94.5 GW of electricity in the hydropower sector, but only a few can be utilized, which is only 11%. This study aims to utilize renewable energy that has not been utilized optimally, especially in Indonesia. This study exploits the potential of water flow from the Coban Wonoasri River, Bangun Village, Munjungan District, Trenggalek Regency which has a low head but has a fairly heavy discharge. The basin cone for making vortex flow has a canal length of 1450 mm, a canal width of 231.5 mm, and a canal height of 500 mm with a basin cone diameter of 560 mm, a basin cone height of 700 mm, and a water outlet diameter of 90 mm. A vortex turbine with a diameter of 270 mm and a height of 210 mm with a total of 8 blades, a blade curvature of 30°, and a blade tilt of 22.5° was used for research on this low head river. The inlet notch variations that will be used are angles of 0°, 17.82°, 19.30°, and 19.98°. The method used in this study is the experimental method, where the best results are obtained from the results of tests carried out on variations in the inlet notch. The inlet notch with a width of 0° and a discharge of 8.81 l/s cannot produce turbine rotation because the vortex flow is not formed properly. Inlet notch with a width of 17.82° and 19.30° produces an average turbine speed of 157.2 rpm and 159.2 rpm. The variation of the inlet notch with a width of 19.98° produces the best turbine speed of 162.7 rpm with a flow rate of 7.72 l/s.
Evaluating of a Super Bright LED as a Spectrophotometer Light Source at The Clinical Laboratory Rangga Santoso; Dyah Titisari; Prastawa ATP; Her Gumiwang Ariswati; Nora Bouzeghaia
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.3

Abstract

Spectrophotometers generally use a halogen lamp as a light source that passes through a filter (wavelength) according to the material to be analyzed. This study aims to analyze the ability of the LED as a light source on a spectrophotometer. In this study, the authors have determined blood sugar parameters as the test material. So that the determination of the wavelength of the LED as a light source must be adjusted to the specifications of the wavelength in the reagent manual procedure used. In the BAV Greiner Glucose Reagent procedure, the allowable wavelength is between 500 - 570 nm with a cuvette thickness of 1 cm. Measured against the reagent blank by the endpoint method. From this reference, the author uses an LED light source with a wavelength of 530 nm, Epistar brand green. The module in this study consisted of a 530 nm LED lamp as a light source, then a lens was added to focus the light beam from the 530 nm LED. The author also adds a Slit / Aperture or it can be called a small hole so that the light passing through is focused at one point of the circle and is passed to the cuvette. The results of the absorption of light will be received by the light sensor (photoresistor) and the data is processed by Arduino and the results are displayed on the display. From the results of this study, the value ranges error from 1% to 3% when a comparative test is carried out with the Analyticon type Biolyzer100 spectrophotometer with 6 different samples and is repeated 5 times each. From these data, it is found that the LED with a wavelength of 530 nm is effective as a light source for checking blood sugar.
A Prototype of Smart Agriculture System Using Internet of Thing Based on Blynk Application Platform Badri Narayan Mohapatra; Rohan Vilas Jadhav; Ketan Sunil Kharat
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.2

Abstract

The research presents the use of the concept of Internet of Things in monitoring the crops and using it in other agricultural purposes. The field of agriculture has always demanded high standards of resources, professionalism and effort. Today majority of the world depends on agriculture for food consumption, economic growth, trade and employment. It also comes with various set of challenges for the agriculturists. Various agriculturists, famers, and scientists across the globe believe in formulating different plans and ideas to deal with these challenges. Smart farming system which is based on fastest growing Internet of Things (IOT) technology which will be cheaper and more productivity and cost effective. In this research we are focusing of handling various information about the crops under consideration and undertake required commands of the user, for a better management of the crops and the resources. Hence providing the agriculturists across various domains a robust and useful capability. Also promoting research and further exploration in the field of use of electronics and internet technology in agriculture.
Artificial Intelligence: A Review of Progress and Prospects in Medicine and Healthcare Saurav Mishra
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.1

Abstract

Andrew NG, a leading philosopher in the field of Artificial Intelligence (AI) once quoted “AI is the new electricity” which has the potential to transform and drive every industry. The most important driving factor for the AI transformation will be data. Clive Humby, a data science entrepreneur was once quoted saying “data is the new oil” and data analytics being the “combustion engine” will drive the AI led innovations. The rapid rise of Artificial Intelligence technologies in the past decade, has inspired industries to invest in every opportunity for integrating AI solutions to their products. Research, development, and innovation in the field of AI are shaping various industries like automobile, manufacturing, finance, retail, supply chain management, and education among others. The healthcare industry has also been adopting the ways of AI into various workflows within the domain. With the evolution in computing and processing powers coupled with hardware modernizations, the adoption of AI looks more feasible than ever. Research and Innovations are happening in almost every field of healthcare and hospital workflows with the target of making healthcare processes more efficient & accessible, increase the overall state of healthcare, reduce physician stress levels, and increase the patient satisfaction levels. The conventional ways in which healthcare and clinical workflows have been operating are now starting to see the change with the integration of many data driven AI solutions. The digital innovations are making life easy for healthcare professionals allowing them to spend more time listening to the problems of patients and consequently increasing the patient satisfaction levels. However, there are limitations and concerns on security of Protected Health Information which have to be addressed for a seamless amalgamation of AI systems into the healthcare domain. Many papers have been published which mostly talk about one particular field/problem in the healthcare domain. No publications have covered the opportunities provided by AI technologies to the entire healthcare domain. This review paper discusses in detail about the progress AI has been able to make in the healthcare domain holistically and what the future of AI looks like. The paper also discusses about the implementation opportunities various AI technologies like Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Computer Vision provide in different fields of healthcare and clinical workflows and how Artificial Intelligence systems will boost the capabilities of healthcare professionals in restoring the human touch in patient-physician encounters. A physician’s intuition and judgement will always remain better suited since each case, each health condition, and each person is unique in its own way, but AI methods can help enhance the accuracy of diagnosis, assist physicians in making improved and precise clinical decisions.

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