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Jurnal E-Komtek
Published by Politeknik Piksi Ganesha Indonesia
ISSN : 25803719     EISSN : 26223066     DOI : https://doi.org/10.37339/e-komtek.v4i2.269
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal E-Komtek (Elektro-Komputer-Teknik) is a Journal that contains scientific articles in the form of research results, analytical studies, application of theory, and discussion of various problems relating to Electrical, Computer, and Automotive Mechanical Engineering.
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 31 Documents
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Search results for , issue "Vol 8 No 2 (2024)" : 31 Documents clear
Sistem Pendukung Keputusan Calon Penerima Beasiswa Yayasan Politeknik Kesehatan Bhakti Setya Indonesia Menggunakan Metode SAW Dan TOPSIS Senoaji, Muhammad Senoaji Wibowo; Enny Itje Sela; Apriyaldi Lukman; Ferryma Arba Apriansyah; Olwin Kirab Novaldy
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2183

Abstract

The scholarship selection system at the Bhakti Setya Indonesia Health Polytechnic Foundation is still conducted manually, making it less transparent and time-consuming. This process requires an objective and measurable method to ensure fairness in determining scholarship recipients. This study aims to develop a decision support system for scholarship selection using the Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The SAW method calculates scores based on the aggregation of weighted normalized values, while the TOPSIS method evaluates candidates based on their proximity to ideal solutions. The criteria used in this study include parental income, number of dependents, GPA, organizational involvement, and achievements. The results indicate that the developed system is capable of ranking candidates with high accuracy. Candidates with the best performance consistently ranked at the top in the results of both methods.
A, The RANCANG BANGUN PENDETEKSI Marsudi Tangguh Dwi Sasongko; Rini Suwartika
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2184

Abstract

Abstract : PMI is a humanitarian organization with legal entity status, governed by Law number 1 of 2018 concerning Red Cross activities, aimed at preventing, avoiding, and alleviating the suffering of war prisoners and disaster victims without discrimination of religion, nationality, race, skin color, group, gender, and political views. PMI also has the duty to transform its members into volunteers. This includes Disaster Preparedness and Response Volunteers, First Aid Training for Volunteers, Health Services, Community Welfare Services, and others. In community services, especially first aid services, PMI still requires more first aid equipment to support the performance of volunteers and their services. One such tool is used for emergencies, such as handling sudden cardiac arrest victims. This study developed a prototype heart rate detection device. This heart rate detection prototype is based on ATmega328. The sensor used is a Heartrate Sensor that functions to measure and detect heartbeats. Additionally, an ATmega328 Arduino Pro Mini microcontroller is used to process the incoming signals and display the heart rate per minute on an OLED screen. Based on tests conducted on 10 respondents, this heart rate detection prototype has an average relative error of 0.32% compared to the Elitech Mobile Fox 1 Pulse Oximeter. Keywords : ATmega328, Heart Rate, Heartrate Sensor.
Application of Deep Learning YOLO in IoT System for Personal Protective Equipment Detection Nugroho, Waluyo; Rifdah Zahabiyah; Afianto; Mada Jimmy Fonda Arifianto
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2187

Abstract

The use of Personal Protective Equipment (PPE) is a critical step in ensuring worker safety in various sectors, including industry, construction, and health. However, violations in using PPE often occur, which can increase the risk of work accidents. This study aims to develop a deep learning-based PPE detection system using the YOLOv8 algorithm. This method was chosen because of its superior ability to detect objects in real time with high accuracy. The training data consists of various images of workers in different work environments, label to recognize types of PPE such as helmets, masks, and safety vests. The developed system was tested on a test dataset to evaluate model performance based on metrics such as confusion matrix, inference speed, and detection error rate. The experimental results show that the YOLOv8 model can detect PPE with an accuracy level of up to 95%. The implementation of this system is expected to be an effective solution in increasing compliance with the use of PPE and preventing work accidents.
The Welding Defect Analysis on ASTM A106 Grade B with Inconel 82 Using Metallography Test and Microhardness Test Muliawan, Arief; Ilmianih, Rizki
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2195

Abstract

Welding inspection is an important practice to assess the integration of structures and their components in many industrial applications. The quality of industrial pipes must be able to withstand high pressures and temperatures, such as in the riser tube primary reformer. In this study, inspection of welding results on ASTM A106 grade B pipes with Inconel 82 using metallography and microhardness was carried out. Based on the results of visual tests and penetrant tests, cracks were found in the meeting area between the Inconel 82 weld and ASTM A106 grade B. The results of the metallography test in the meeting area between Inconel 82 and ASTM A106 grade B showed continuous microcracks and continuous macrocracks. The results of microhardness testing in the area around the crack had a lower hardness value than the area far from the crack. The welding connection of ASTM A106 grade B with Inconel 82 could not be used optimally at a temperature of 748oC because Inconel 82 has a silicon element of 0.5% which causes a difference in solidification between ASTM A106 grade B and Inconel 82
Implementation of Random Forest Algorithm for Classification of Eligibility For Social Assistance Recipients In Information Systems Mita Trianda; Triase Triase
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2197

Abstract

This study aims to develop a web-based information system for classifying the eligibility of social assistance (BANSOS) recipients using the Random Forest algorithm in the Bagan Batu Kota Subdistrict. The system is designed to assist local authorities in identifying BANSOS recipients more accurately and efficiently, minimize errors, and enhance distribution fairness. A quantitative research method was employed, with data collection techniques including observation, interviews, literature review, and document analysis. The dataset consists of 1,100 samples with features such as income, family size, and housing conditions. The Random Forest algorithm was implemented by building a classification model based on training and testing data. The evaluation showed a system accuracy rate of 97%, with a classification error of only 3%. The system provides features for recipient data management, field validation, and automated reporting, supporting more precise decision-making. The results of this study are expected to offer a solution for more effective and transparent social assistance distribution.
Analysis of Water Quality Parameters on the Survival Rate of Vannamei Shrimp using the Random Forest Method Prih Diantono Abda'u; Ratih Hafsarah Maharrani; Zaenurrohman; Adrian Putra Ramadhan
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2215

Abstract

This study developed a predictive model based on Random Forest algorithm to predict survival rate of Vannamei shrimp using five water quality parameters: dissolved oxygen (DO), temperature, pH, salinity, and Total Dissolved Solids (TDS). The model was trained on this data and evaluated using Mean Squared Error (MSE) and R² Score, with an MSE of 0.71 and R² Score of 1.00. Endpoint testing was conducted using Postman to verify the model response, with output parameters including anomaly_detected, recommendation, and survival rate. The model successfully detected anomalous conditions and provided recommendations according to the detected water quality parameters. Test results showed that DO and salinity had the greatest influence on survival rate, while pH, TDS, and temperature made moderate contributions.
Water Turbidity Detection Device Using Turbidity Sensor Based On Arduino Uno Noviasari, Linda; Asni Tafrikhatin; Juri Benedi; Vicky Oby Syahputra
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2219

Abstract

A water turbidity detector using an Arduino Uno based turbidity sensor is a solution to measure water turbidity. The turbidity sensor functions to measure the level of water turbidity by detecting dissolved solid particles in it. The use of Arduino Uno as the main microcontroller, turbidity sensor to measure the level of turbidity and the results can be displayed clearly on the LCD. The main advantage of this tool is its ability to provide information about water turbidity. The integrated LED and Buzzer also provide notification if the water turbidity level has been set. In addition, the simplicity of use and integration between the turbidity sensor, Arduino Uno, LED, LCD, and buzzer on one microcontroller board provides convenience for users. The outputs of this system are LCD, LED and buzzer, and the entire input-output system is integrated by one arduino uno microcontroller board. This system is designed to assist users in detecting turbidity using a turbidity sensor. Based on testing, the success rate of this system is 93.27%.
Design and Build E-Stm Using Real-time Push Notification in Sumber Padi Village Wulandari, Novika; Samsudin, Samsudin
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2228

Abstract

Relief societies (STM) are important in helping people in need through various social programs and activities.This study addresses the issue of STM member logging and financial data management, then addressing misinformation reported by managers or citizens and making it easier for citizens to pay STM dues. This study uses Firebase Realtime database for data storage and Firebase Storage to store photo media; Research and development methods (R&D used as a method in this study, and uses the Rapid Application Development (RAD) method as its system development method. The author also uses Realtime push Notification by using firebase cloud messaging to build STM applications. The results of the black box system test show that the application runs by the needs of the system, the research carried out has high relevance to facilitate the management of member data, contributions and activity information on STM.
Geographic Information System in Web-Based Disease Spread Mapping in Public Hospitals Febriansah Siregar, Bayu; Ikhwan, Ali
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2231

Abstract

The application of web-based Geographic Information Systems (GIS) in mapping the spread of diseases at Kotapinang General Hospital aims to improve the effectiveness of health data management and response to disease outbreaks. With a large population and significant health challenges, Indonesia needs a real-time system to monitor and analyze disease spread. This research develops a GIS system that utilizes Google Maps API to visualize epidemiological data, identify high-risk areas, and provide relevant information to health workers. The research methodology includes disease data analysis, database design, and system testing. The study results show that this system not only increases hospitals' capacity to manage health data, but also accelerates decision-making in disease control. Despite data quality and user skills challenges, this web-based GIS offers a significant solution for health management in South Labuhanbatu Regency. This study recommends further development to improve the features and accessibility of the system.
Sistem Berbasis Penalaran Kasus untuk Deteksi Penyakit Tourette Syndrome Abdurrasyid; Indrianto, Indrianto; Meilia Nur Indah Susanti; Rima Rizqi Wijayanti
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2232

Abstract

Tourette Syndrome (TS) is a neurological disorder affecting children under 18, with an estimated prevalence of over 150,000 cases annually in Indonesia and 1% globally. Misdiagnosis rates of 20-30% complicate effective management. TS involves involuntary, repetitive tics, ranging from sudden movements or sounds to aggressive behaviors, posing significant challenges for diagnosis and treatment. This study utilizes an expert system with a case-based reasoning (CBR) approach to improve TS diagnosis. Interviews with TS patients and specialists provided data on symptoms and diagnostic structures. A weighting mechanism and an accumulation formula were implemented to deliver accurate diagnostic outcomes and first aid suggestions, optimized for minimal computing resources without reliance on extensive datasets. Testing on 10 patients, under expert supervision, demonstrated the system's ability to accurately diagnose and classify TS. The system effectively simulates expert-level TS detection, offering precise diagnosis and recommendations, potentially enhancing early intervention and reducing diagnostic errors.

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