Jurnal Teknokes
The JURNAL TEKNOKES is a peer-reviewed periodical scientific journal aimed at publishing research results of the medical engineering areas. The Journal is published by the Department of Medical Electronics Technology, Health Polytechnic of Surabaya, Ministry of Health Indonesia. The role of the Journal is to facilitate contacts between research centers and the industry. The aspiration of the Editors is to publish high-quality scientific professional papers presenting works of significant scientific teams, experienced and well-established authors as well as postgraduate students and beginning researchers. All articles are subject to anonymous review processes by at least two independent expert reviewers prior to publishing on the Jurnal Teknokes website. This journal focuses on the development of the: (1) Medical Electronics Technology and Biomedical Engineering; (2) Medical Laboratory Technology; (3) Environmental Health, Engineering and Technology; (4) Health Information System and Technology.
Articles
12 Documents
Search results for
, issue
"Vol 15 No 4 (2022): December"
:
12 Documents
clear
<![CDATA[Biomedical Waste Management among Primary Health Care Workers, Bauchi Local Government Area, Bauchi State, NIGERIA ]]>
<![CDATA[Yusuf Sarkingobir]]>;
<![CDATA[Asiya Gidado Yabo]]>;
<![CDATA[Safina Abdullahi Yarima]]>;
<![CDATA[Yusuf Yahaya Miya]]>;
<![CDATA[Ibrahin Friday Sule]]>;
<![CDATA[Nabil Riskuwa Bello]]>;
<![CDATA[Abubakar Shehu]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.348
<![CDATA[Biomedical waste management is a serious issue to health and environment that must be addressed at primary health care level, especially in Bauchi local government area of Bauchi state. The objectives of this study were to assess on the knowledge, methods and problems of biomedical waste management among the primary health care workers in some selected Health Care Centers of Bauchi L.G.A. of Bauchi state. A cross sectional study was employed and sampling techniques were used to distribute a questionnaire and interview among the health workers at twenty (20) selected primary health centers with (200) sample respondents from public and private health care centers. The result from the current study shows that the knowledge of biomedical waste management awareness among the workers was represented (94%), and only (6%) were not aware. The majority of PHC workers practiced open dumping and burning method (74%), incineration (7%), chemical treatment and only 1% for autoclave methods. while, microwaving (0%), encapsulation (0%) and sanitary landfill methods (0%) were not practiced. The problems of biomedical waste management included improper planning (33%), insufficient funds (25%), lack of material (19%) and (15%) lack of staffs training. There was improper segregation, lack of planning, lack of funds and practiced open dumping and burning, which is against the biomedical Waste (Management and Handling) Rules of 2016. There was improper biomedical waste management at primary health care level in Bauchi local government of Bauchi state. Thus, the Bauchi government should give more consideration towards good plan, allocation resources, set a committee of adequate supervision, monitoring and evaluation for the sustainable biomedical waste management at Bauchi local government of Bauchi state. .]]>
<![CDATA[A Non-invasive Approach to Detection Blood Glucose Levels with Hand Skin Image Processing Using Smartphone ]]>
<![CDATA[Usman Umar]]>;
<![CDATA[Risnawaty Alyah]]>;
<![CDATA[Mustapa Mustapa]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.444
<![CDATA[Measuring blood sugar levels today still use invasive techniques that are painful so non-invasive monitoring is needed. This study aims to develop a non-invasive technique to identify and detect blood glucose through hand-skin image processing. This development method is by taking invasive blood glucose hand images and 30 participants aged 20-60 years, data analysis is done by image preprocessing, determining the Gray level co-occurrence matrix (GLCM) value, using the backpropagation algorithm to conduct training and data testing. to define a blood glucose monitoring model. The blood glucose detection model is implemented through the android operating system on smartphones by developing the GULAABLE application on smartphones which is simple and easy to use and without blood sampling. This GULAABLE application is to determine the condition of low or high blood glucose and can be used routinely at a low cost. Validating the results by identifying this non-invasive application compared with the results of invasive glucose measurements by applying to 10 participants, the identification results show an accuracy of 80%, so it can be concluded that the GULAABLE application method on smartphones can be used to monitor blood glucose conditions at any time by simply taking hand skin image.]]>
<![CDATA[Design of a Safety Device Ultra Violet Light for Mercury Identification in Whitening Cream with Thin Layer Chromatography Method Using Camera OV7670 Based on Arduino Uno ]]>
<![CDATA[Hasmah Hasmah]]>;
<![CDATA[Risnawaty Alyah]]>;
<![CDATA[Usman Umar]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.450
<![CDATA[Mercury is also called “air raksa” or hydrargyrum which is a chemical element with the symbol Hg and belongs to the heavy metal group with a liquid form and silvery color. Mercury is a heavy metal that is harmful to the skin when added to cosmetics, especially creams on the face, even in small concentrations because it is toxic. Identification of Mercury in the laboratory using the thin layer chromatography method with the help of ultra violet light causes medical personnel to be vulnerable to exposure to ultra violet rays which have a negative impact on eye and skin health. The purpose of this research is to design a safety to minimize exposure to ultra violet rays when identify mercury. OV76070 which can reduce direct contact with ultra violet light identifies the present of Mercury in the whitening cream will be carried out using a thin layer chromatography separation method with the help ultra violet 254nm-366nm. With the help of ultra violet lamps 254nm-366nm, and it is hoped that Mercury inspection using the OV7670 camera will be more efficient and accurate. The tool used in this research is the OV7670 camera with a power of 640 – 460 pixels (VGA) to take photo on thin layer chromatography plate, ultra violet lamps 254nm- 366nm. Overall the design of this tool is controlled by the Arduino Uno microcontroller. Image from the OV7670 camera can be monitored at the Liquid Crystal Display in the form of the appearance fluorescence spot indicating the presence of Mercury in the whitening cream sample.]]>
<![CDATA[Comparison of GLCM and First Order Feature Extraction Methods for Classification of Mammogram Images ]]>
<![CDATA[Ega Elfira]]>;
<![CDATA[Wahmisari Priharti]]>;
<![CDATA[Dien Rahmawati]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.458
<![CDATA[Breast cancer is one of the main causes of death in women and ranks first in cancer cases in Indonesia. Therefore, an early detection and prevention of breast cancer is necessary, one of which is through mammography procedures. A machine learning classifier such as Support Vector Machines (SVM) could be used as an aid to the doctors and radiologist in diagnosing breast cancer from the mammogram images. The aim of this paper is to compare two feature extraction methods used in SVM, namely the Gray Level Co-Occurrence Matrix (GLCM) and first order with two kernels for each method, namely Gaussian and Polynomial. Classification using SVM method is carried out by testing several parameters such as the value of C, gamma, degree and varying the pixel spacing values in GLCM, which usually in previous studies only used the default pixel spacing. The dataset consists of 500 mammogram images containing 250 benign and malignant images, respectively. This study is expected to find out the best method with the highest accuracy between these two texture feature extractions and and able to distinguish between benign and malignant classes correctly. The result achieved that Gray Level Co-Occurrence Matrix (GLCM) feature extraction method with both Gaussian and Polynomial kernel yields the best performance with an accuracy of 89%.]]>
<![CDATA[An Improved Design of Flat Panel Detector with Phototransistor PH101 Analysis of The Tube Voltage Setting ]]>
<![CDATA[Nina Havilda]]>;
<![CDATA[Muhammad Ridha Mak'ruf]]>;
<![CDATA[Tri Bowo Indrato]]>;
<![CDATA[Sedigheh Asghari Baighout]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.464
<![CDATA[The intensity and quality of the X-Rays a patient receives is determined by the exposure factor. Voltage (kV), Current (mA), Time (seconds), and tube-to-film distance (FFD) are exposure factors that can be controlled and determined. The key factor that can determine the quality of X-Rays is the tube voltage (kV) which affects the X-Rays to penetrate objects. The purpose of this research is to improve image quality and relatively affordable manufacturing costs by obtaining the difference in the detector catch value between dark and light by utilizing the response of the PH101 phototransistor sensor. The contribution of this research is that the system can display grayscale and numeric on a 16x16 pixel matrix using the Matrix Laboratory (MATLAB) application. This research can convert images taken from analog data after measuring the phototransistor PH101 on X-Rays. The measurement settings used are 50, 55, 60, and 70kV, with a tube current of 40 mA and an irradiation time of 1 second. The measurement results show that the Flat Panel Detector Design can respond to differences in doses and objects. This research shows that a Flat Panel Detector and a Phototransistor PH101 sensor have been successfully made which can be used to capture X-Rays so that the black level of the film can be determined.]]>
<![CDATA[Analysis of Transmitted and Received ECG Signal Based on Internet of Thing Using Web Browser and Server-Client HTML Protocol ]]>
<![CDATA[Dewi Rushalina]]>;
<![CDATA[I Dewa Gede Hari Wisana]]>;
<![CDATA[Priyambada Cahya Nugraha]]>;
<![CDATA[Nazila Ragimova]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.469
<![CDATA[Cardiovascular disease is one of the leading causes of death worldwide. One of the reasons for the large number of deaths from heart disease is the lack of regular cardiac monitoring. Electrocardiograph (ECG) is a method of monitoring heart conditions. There are still many ECG examinations in hospitals that are carried out directly in certain places and the results can only be seen at that time. Meanwhile, when negligence or carelessness occurs, it can endanger the patient due to delays in handling. One of the efforts that can be made to improve service to heart patients is by having ECG monitoring based on IoT (Internet of things). The purpose of this study is to analyze the ECG signals sent and received by IoT media so that they are useful for the diagnostic process. The contribution of this research is to know the shape of the ECG signal that is sent and received through IoT media. The procedure to achieve this goal is with the AD8232 sensor whose output will be processed through the microcontroller and displayed on computer and smartphones via IoT. From this research, the results obtained that the average value of lost data at BPM 60 and BPM 120 is quite good, namely 21.26% and 24.44%.hile the average time delay value at BPM 60 and BPM 120 is also quite good, namely 0.023 s and 0.03 s. So, it can be concluded that the sending of IoT-based ECG signals affects the form of signals sent and received. The results of this study are expected to be developed in further research with development in the form of adding leads or adding BPM parameters.]]>
<![CDATA[High Flow Oxygen Analyzer Design on High Flow Nasal Cannula (HFNC) for Monitoring Oxygen therapy in Adults ]]>
<![CDATA[Rifan Amirul Fatkhur Rokhman]]>;
<![CDATA[Tri Bowo Indrato]]>;
<![CDATA[Endang Dian Setioningsih]]>;
<![CDATA[Shubhrojit Misra]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.470
<![CDATA[High Flow Nasal Canulla (HFNC) is a technique that provides a high flow of heated and humidified gas. HFNC is simpler to use and implement than noninvasive ventilation (NIV) and appears to be a good alternative treatment for hypoxemic acute respiratory failure (ARF). This study aims to help facilitate medical personnel or equipment operators in monitoring the flow that enters the patient's body so that oxygen therapy can be given according to the right dose. This study uses an Arduino microcontroller to process the output flow from the Sensirion SFM-3000 flow sensor, then the processed flow value will be displayed on the TFT LCD. The independent variable in this study is the flow setting value, while the dependent variable is the SFM-3000 flow sensor. The largest error flow value is in the setting at 30 LPM with an error value of 2.70%. The flow value is set using a flowmeter, while the comparison tool used is a flow analyzer (Citrex H3). In the testing phase, the measurement value is 10 LPM to 60 LPM with a time of 5 minutes at each point. Based on the measurements that have been made, the largest error value is obtained at the value of 30 LPM, which is 2.70% and the smallest error value is at the value of 60 LPM, which is 0.74%. Data retrieval using a compressor and central oxygen is very influential on the results of the flow and oxygen concentration. The results obtained are more stable than without the use of a compressor and central oxygen.The conclusion from these results is that the calibrator module has a relative error (error value) that is still within the allowable tolerance limit, which is ±5%. And also the design of this tool is portable and low cost and is made to be used in hospital agencies as a support for maintenance on HFNC equipment]]>
<![CDATA[Design and Build a Ventilator Tester with a Peak Inspiratory Flow Waveform Display as Validation using the F1031V Sensor ]]>
<![CDATA[Rusdi Pratiwo Hadi]]>;
<![CDATA[Her Gumiwang Ariswati]]>;
<![CDATA[Dyah Titisari]]>;
<![CDATA[Syaifudin Syaifudin]]>;
<![CDATA[Sari Luthfiyah]]>;
<![CDATA[Bedjo Utomo]]>;
<![CDATA[Liliek Soetjiatie]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.472
<![CDATA[The ventilator is a supporter of respiratory needs which is very important for the patient so that there are several parameters that must be monitored specifically, such as the measurement of pressure and flow rate used in the ventilator system, the accuracy of which must be in accordance with the accuracy of the respirator. One of the important parameters to monitor is PIF (Peak Inspiratory Flow) which is the peak inspiratory flow rate given through the ventilator. PIF that is too high or too low can cause adverse effects on the patient. PIF monitoring can be seen through the PIF value and waveform on the PIF. Monitoring the waveform of the PIF will be very useful to improve the results of using the ventilator. The purpose of this research is to get the accuracy and precision of the sensor to display the waveform of the ventilator output. The procedure carried out is to use the F1031V sensor to detect the flow generated by the ventilator and then detect the PIF value and PIF waveform. From this research, the measurement of accuracy and precision of the F1031V sensor to detect PIF and generate a waveform graph is said to be good. This is because the highest error value is ±2.04% at the 20 LPM setting. While the value of the largest standard deviation at the 30 LPM setting is 1.517 and the greatest uncertainty value at the 30 LPM setting is 0.061. Then, the largest correction value is found in the setting of 20 LPM and 30 LPM, namely 0.4. PIF monitoring is carried out to maximize patient care and reduce the breakdown time on the ventilator.]]>
<![CDATA[Implementation of Gyro Accelerometer Sensor for Measuring Respiration Rate Based on Inhale and Exhale Using Kalman Filter ]]>
<![CDATA[Fitriyana Jayanti]]>;
<![CDATA[Triwiyanto Triwiyanto]]>;
<![CDATA[Triana Rahmawati]]>;
<![CDATA[Abdussalam Ali Ahmed]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.479
<![CDATA[Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions including heart, lung, emotional stress, the influence of body temperature and activity fatigue. The respiratory rate in humans is measured by counting the number of breaths for one minute by monitoring and counting the number of times the chest rises and falls during the inhale and exhale process. Various methods for measuring respiratory rate that are commonly used including pneumograph, impedance and capnography are applied in patient monitoring. This study aims to examine and analyze the application of the kalman filter on the output of the gyro accelerometer sensor to increase the results of the detection of respiratory rates using the gyro accelerometer sensor. This study test was carried out using a patient simulator in Surabaya Ministry of Health Polytechnic nursing laboratory. This simulator patient can simulate respiration with a mechanical work system up and down the chest and abdomen, uses an Arduino Nano microcontroller to filter the output of the gyro accelerometer sensor and the results will be compared before and after the filter. The independent variable in this study is the respiration value, while the dependent variable is the sensor output before being filtered. In the relaxed condition of the respondent The most effective use of the kalman filter is found in the parameters R = 10, Q = 0.1 because in the use of these parameters, the value after being filtered has a value that tends to be stable. The highest error value in the application of the gyro accelerometer sensor occurs at sensor position 1 with R = 1 Q = 10 value of 2,6%. This study shows the effect of differences in respiration values before and after using a kalman filter. This study has limited differences in values that are far between the pre filter and after being filtered in several data collections.]]>
<![CDATA[Negative Pressure Gauge on a Suction Pump Equipped with MIT APP Inventor-Based Measurement Data Input and Storage ]]>
<![CDATA[Kartika Aryadiny]]>;
<![CDATA[Nur Hasanah Ahniar]]>;
<![CDATA[Andy Sambiono]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35882/teknokes.v15i4.486
<![CDATA[Research conducted by Muhaji, Bedjo Santoso, Putrono on the comparison of the effectiveness of two levels of suction pressure on oxygen saturation in endotracheal tube patients. The findings show that there is a significant effect of negative pressure on oxygen saturation. So that the use of the pressure value must be ensured that it is appropriate so as not to injure the patient. The accuracy and accuracy of the pressure value can be ensured by calibrating the suction pump with a calibrator, namely Digital Pressure Meter. From this case, a digital pressure meter module was created with an application. This tool serves to read the pressure value on the suction pump in real time. This tool was created with the aim of measuring negative pressure on a suction pump which is equipped with an application for inputting and storing measurement data based on the MIT App Inventor to make it easier for users to input tool identity and calibration results. To get results that are in accordance with the purpose of writing, using the study method to the library, the preparation stage, the design stage includes making software and hardware, then testing and measuring. Negative pressure measurement testing uses a Suction Pump as a measurement sample and uses 2 comparison tools, namely DPM4 and Manometer. Negative pressure testing was carried out 10 times at each measurement point, namely -10.6, -20, -30 kPa and -80, -150, -225 mmHg. After the measurements were taken, it was concluded that the module test compared to DPM4 obtained an accuracy of 99.09%, while the module test compared to the Manometer obtained an accuracy of 98.85%. Pressure measurement compared to DPM4 has 0.24% higher accuracy than pressure measurement developed with Manometer. This module is designed to be used for power calibration specifically for Suction Pump equipment. To make it easier to use the TFT nexion LCD.]]>
