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All Journal Elektrika Jurnal Ekonomi Manajemen Sistem Informasi Jurnal Keperawatan Sisthana Journal of Innovation Research and Knowledge Journal of Engineering, Electrical and Informatics
Bayu Wahyudi
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Law, Crime, Criminology & Criminal Justice Nursing Public Health Social Sciences

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Journal : Journal of Engineering, Electrical and Informatics

 1 
Classification of Skin Cancer Diseases Using KNN, CNN and SVM Methods Mohamad Sofie; Mohammad Rofi’i; Bayu Wahyudi
Journal of Engineering, Electrical and Informatics Vol. 5 No. 2 (2025): June: Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i2.3844

Abstract

According to the WHO, about 2 to 3 million non-melanoma.non-melanoma skin cancers and 132,000 melanoma skin cancers occur globally every year, making up one out of every three cancers.globally each year, and account for one in every three cancers diagnosed.diagnosed. In Indonesia, skin cancer is listed as the cancer with the third highestincidence after uterine cervical and ovarian cancer, and breast cancer.Skin cancer can be detected with dermoscopy. Dermoscopy is a non-invasive diagnostic technique using optical magnification that allows visualization of morphologicHowever, this cannot be done optimally because it still relies on manual analysis so it cannot classify skin cancer types on larger datasets with potential errors and low accuracy. To accurately determine the type of skin cancer,a better classification method is needed. The purpose of this research is to determine the accuracy of skin cancer calcification using Convolutional Neural Network (CNN), support vector machine (SVM), K-nearest neighbor (KNN) models. The datasheet used amounted to 2,239 containing skin cancer images with class division 114 actinic keratosis, 376 basal cell carcinoma, 95 dermatofibroma, 438 melanoma, 357 nevus, 462 pigmented benign, 77 seborrheic keratosis, 181 squamos cell, 139 vascular lesion. The results showed that the convolutional neural network (CNN) algorithm model obtained a sensitivity of 92.59%, specificity of 99%, precision of 93%, F1-Score of 93.01%, and accuracy of 98.35%. For the KNN algorithm model, 57.77% sensitivity, 94.53% specificity, 64.25% precision, 55.99% F1-Score, and 90.45% accuracy were obtained. And for the SVM algorithm model, 61% sensitivity, 94.81% specificity, 70.23% precision, 61.26% F1-Score, and 91.17% accuracy were obtained.
Mindray Anesthesia Machine Repair Type Wato Ex-65 at Columbia Asia Special Surgery Hospital Semarang Andy Setiawan; Pramesti Kusumaningtyas; Bayu Wahyudi
Journal of Engineering, Electrical and Informatics Vol. 5 No. 2 (2025): June: Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i2.4165

Abstract

Anesthesia machines are very important medical equipment in modern medicine, especially in medical procedures and intensive care. This device is designed to provide and control the administration of anesthetic drugs and medical gases to patients safely and accurately. Damage to the oxygen regulator block of the anesthesia machine shows a discrepancy with the indicator reading. This problem is very critical because it can cause the administration of inappropriate oxygen concentrations to patients during anesthesia procedures. This activity aims to support health services at the Columbia Asia Semarang Hospital which has a damaged anesthesia machine and wants to be repaired, namely the Mindray Type Wato EX-65 anesthesia machine. Damage to the device is known by disassembling the device, by visual observation, checking for hose leaks, and measuring at certain points in the device circuit. Based on the analysis carried out, the damage is in the anesthesia machine regulator block. After repairs and functional tests using VT 305 to check the air flow, it was declared suitable for use.
Simple Medical Waste Incinerator Design and Construction Bayu Wahyudi; Muhammad Iqbal Maulana; Mohammad Rofi’i
Journal of Engineering, Electrical and Informatics Vol. 5 No. 2 (2025): June: Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i2.4359

Abstract

Medical waste management is a major concern in protecting public health and the environment. This study aims to design and test a simple medical waste incinerator controlled by a microcontroller, intended for use in small-scale healthcare facilities. The method used was research and development (R&D), involving need analysis, system design, hardware assembly, and performance testing of the components and waste combustion effectiveness. The results indicate that the system operates stably with voltage error rates below 1% and high temperature sensor accuracy. The incinerator achieved an average combustion effectiveness of 95% across four types of disposable medical waste. The tool can operate automatically based on temperature and time settings, utilizing readily available and energy-efficient electronic components. These findings suggest that the developed incinerator is suitable as an alternative solution for medical waste treatment in clinics or health centers and has potential for further development into an environmentally friendly and sustainable incineration system.
Arduino Uno Based Audiometer Design Mohamad Sofie; Muhammad Rizky Aditya Firdaus; Bayu Wahyudi
Journal of Engineering, Electrical and Informatics Vol. 5 No. 2 (2025): June: Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i2.4828

Abstract

The ability to detect hearing impairment early is an important aspect of preventive efforts in the field of ear and hearing health. An audiometer is a device used to measure a person's hearing threshold by presenting sound stimuli at various frequencies and intensities. This research aims to design and build a simple digital audiometer that can be used as a means of early hearing screening at primary healthcare facilities. The developed audiometer system uses a microcontroller as the control center, equipped with a user interface based on an LCD screen and buttons for adjusting frequency and sound intensity. Sound output is channeled through headphones and calibrated within the frequency range of 125 Hz to 10,000 Hz with intensity levels from 0 dB to 10 - 100 dB. The value obtained from the measurements after making improvements on TP 1 (Input adapter) showed an error of 0.03% TP 2 (Nextion LCD input) at 5.12 V which is still within tolerance. TP 3 (Arduino Input) at 11.64 V which is still within tolerance. TP 4 (Input IC LM2956) at 11.66 V which is still within tolerance. The function of this audiometer tool was tested using a digital multimeter. The highest error value is at a frequency of 500 Hz, which is 0.152%. This is partly due to the tolerance values of the components used. Based on the data collection using a sound level meter, the furthest difference in sound intensity values at the point of 40 dB was found to be 3.46 dB. This is due to the influence of noise in the surrounding measurement area.
Design and Construction of a Blood Type Detection Device with a Color Sensor Based on Arduino Uno Ilham Qomaruzzaman; Wisnu Adi Prasetyanto; Bayu Wahyudi
Journal of Engineering, Electrical and Informatics Vol. 5 No. 2 (2025): June: Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i2.5145

Abstract

A Blood Type Detector is an electronic device used to detect human blood types. Blood type detection and observation are generally carried out through a series of experiments on blood samples, namely antiserum reactions (anti-A, B, AB, and D). Currently, determining a person's blood type is still done manually. This will certainly be complicated and require extra attention if the blood sample to be tested is quite large in number, it will take a lot of time and is inefficient. The purpose of research on a Blood Type Detector Tool with an Arduino Uno-Based Color Sensor is to improve the efficiency, accessibility, and quality of health care as a whole. As well as ease of access and data processing for users. This tool is designed using a Color Sensor so that it can detect the occurrence of agglutination or non-agglutination reactions from blood samples that have been mixed with antigens. The working system settings of this tool are based on Arduino Uno, the results of which will be displayed on the LCD, then a sound will appear from the results of the blood type being read. In the blood type test function test process, a blood sample and antigen are required, where the blood sample and antigen are mixed together, the ratio is one drop of blood with one drop of antisera, then stirred together, so that agglutination or non-agglutination occurs in the blood sample that has been mixed with the antigen. After sampling, the blood type tester will detect the four blood samples dropped onto the sample card. When the blood sample in anti-A and AB coagulates, the sensor will read a value of >200 for blood type A.
Co-Authors Andy Setiawan Bambang Sukajie Fadhilla Hida Aulia Fransiskus Dicky Septiawan Ichsan Widiyana Ilham Qomaruzzaman Isny Novia Nurkharisma Kahar Mulyani M. Rofi’i Mohamad Sofie Mohamad Sofie, Mohamad Mohammad Rofi’i Muhammad Iqbal Maulana Muhammad Rizky Aditya Firdaus Muhammad Tonidenta Putradwiyuda Nining Handayani Paramita Deniswara Pramesti Kusumaningtyas Wisnu Adi Prasetyanto