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Eko Prasetyo
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JEECS (Journal of Electrical Engineering and Computer Sciences)
Published by Universitas Bhayangkara Surabaya
ISSN : 25280260     EISSN : 25795392     DOI : https://doi.org/10.54732/jeecs
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
We aims to promote high-quality Electrical Engineering and Computer Sciences research among academics and practitioners alike, including power system, electrical engineering, industry automation, mechatronics, computer sciences, informatics, and information system. This journal is dedicated for the author or researcher who has focused in the field of technology and intending on publication and sharing knowledge the novel technology include, but are not limited to, the following topics: Data Mining, Informatics algorithm methodology, Mobile Computing, Automation, Power, Green Technology, Advanced Computer Networks, Image Processing, Computer Vision, Robotics Technology, Decision Support System, Big Data, Data Sciences, Internet of Things, Network Security, Virtual Reality, etc.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 201 Documents
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Detection Diabetic Retinopathy with Supervised Learning Adithya Kusuma Whardana; Parma Hadi Rantelinggi
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 8 No. 2 (2023): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v8i2.7

Abstract

Diabetic retinopathy is a common complication that occurs in people with diabetes mellitus. Diabetic retinopathy damage is characterized in the blood vessel system in the layer at the back of the eye, especially in tissues that respond to light. This research aims to detect diabetic retinopathy early by using SVM and Random forest. SVM is a classification technique that divides the input space into two classes. Random Forest is a supervised learning algorithm that utilizes a collection of decision trees trained using the bagging method. This research uses datasets from diaretdb1 and messidor to evaluate the performance of both methods. The diaretdb1 dataset consists of 178 data points with the diagnosis of Proliferative Diabetic Retinopathy and Non-Diabetic Retinopathy. In addition, the messidor dataset consists of 105 data points with the diagnosis of Diabetic Retinopathy and Non-Diabetic Retinopathy. Experimental results on the diaretdb1 dataset showed that SVM achieved 88% accuracy, while Random Forest achieved 91% accuracy. Similarly, on the messidor dataset, SVM achieved 80% accuracy, while Random Forest achieved 85% accuracy.
Design of Thrift Shop E-Catalog Information System Using PHP and Javascript (Case Study: Meytwins Thrifting) Christina Meylianti; Muhamad Femy Mulya; Pramitha Dwi Larasati; Saipul Anwar
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 8 No. 2 (2023): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v8i2.8

Abstract

Currently, there is a popular trend among the younger generation regarding the use of used clothes. What's interesting is the emergence of the online thrift shop, which is a type of business that is booming in the fashion sector by selling used clothes through online platforms. Generally, these business people get clothing supplies in the form of bales (sacks) imported from abroad. The Online Thrift Shop has received a positive response from many young people by offering clothing that has a unique style in a retro or vintage atmosphere from the 90s, as well as world-famous brands. However, one of the obstacles faced by the online thrift shop is the mismatch between the products received by consumers and what was initially displayed by the seller. There are situations where the goods delivered to consumers do not match the description given by the seller. This phenomenon is one of the shortcomings that need to be considered in online thrift shop operations. There are many online shops that sell goods to consumers that do not match what is offered. This makes consumers' shopping confidence and comfort less comfortable. The aim of the research is to build an information system in the form of an e-catalog that can simplify the buyer process without having to come to the store, as well as provide information related to fashion products that are suitable for consumers or customers. In this research, we used the prototype method, then for the system design tools, we used UML modeling, and for database modeling, we used ERD. Information system built using PHP and Javascript. Then, based on the test results using BlackBox Testing from several respondents, the success rate of the system built was 95%. Keywords: E-Catalog, Prototype, PHP, Javascript, Blackbox Testing
Analysis of Voltage Drop and Power Losses on Medium Voltage 20 KV Distribution System Kotamobagu Area Supplied from PLTD Kotamobagu Yuslizar E.P. Bachari; Yasin Mohamad; Taufiq Ismail Yusuf; Lanto Mohamad Kamil Amali
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.9

Abstract

Drop voltage and power loss at the distribution system of electricity power in the Kotamobagu Area are caused by several factors, a namely far distance of a place that is distributed by electricity power from the source, imbalance load, equipment age, the diameter of the conductor, a distance of powerhouse to the consumer is too far and connection point are caused for technical loss. If it keeps happening, it will decrease the reliability of the electric power system and the distributed quality of the electricity power as well as it can damage the equipment. Therefore, unbalanced loading should be decreased at the phase, and overloading at the network will cause PT PLN (Persero) loss in the Kotamobagu Area. This research aims to analyze voltage drop, percentage of voltage drop, and power loss at every medium voltage feeder of 20 KV that is supplied from PLTD (Steam Power Plant) Kotamobagu until every transformer of distribution at peak load. After it is analyzed, the feeder OK 1, OK 2, OK 3, OK 4, OK 5 obtain the most significant value of drop voltage for 7.221 KV, 1.94 KV, 6.472 KV, 5.04 KV, 4.878 KV, respectively, with a percentage value of 56.507%, 10.742%, 47.841%, 33.689 %,32.257%. All OK happen at powerhouse K-153 (Kobo Besar), K-158 (RS. Monompia Kotamobagu), K-187 (Poopo I), K-201 (Motoboi Kecil), K-287 (Moyag I), respectively. The most significant power loss of 11.890 KW, 4.820 KW, 9.819 KW, 7.311 KW, 10.533 KW happen at powerhouse K-140 (Matali I), K-158 (RS. Monompia Kotamobagu), K-167 (Bilalang V), K-201 (Motoboi Kecil) and K-287 (Moyag I), respectively.
Decision Support System for Determination Exemplary Employees Using Simple Additive Weighting Method (Case Study: BKN Office Yogyakarta) Wahyu Widodo; Siswaya Siswaya; Sony Satya Nugraha
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.4

Abstract

The selection of exemplary employees is an annual event divided into three categories: civil servants, non-civil servants, and outsourced employees. Selection is based on four criteria: performance quality, discipline percentage, moral behavior, and leadership quality. The Assessment Team's assessment process for exemplary employees is carried out by recapitulating the assessment data for each work unit and determining exemplary employees from the recapitulation results using a manual form for evaluating employee performance within BKN Yogyakarta. Manual assessment requires quite a long time and has the risk of errors during the calculation process, so researchers see the need for a decision support system for selecting exemplary employees using the Simple Additive Weighting (SAW) method. This system helps the personnel department quickly and accurately rank exemplary employees. The system calculation results use the SAW method with 6 alternative employees with each score: Sudi 1, Heru 0.9, Vivid 0.82, Anjas 0.82, Tri 0.75, and Suwar 0.5. Sudi received the highest score and was designated as a model employee for this period.
Deep Learning-Based Road Traffic Density Analysis and Monitoring Using Semantic Segmentation Adithya Kusuma Whardana; Parma Hadi Rentelinggi
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.1

Abstract

Due to factors such as a growing population, more people using private vehicles, and outdated transportation infrastructure, Jakarta, the capital city of Indonesia, suffers from chronic traffic congestion. The environment, citizens' safety, productivity, and quality of life are all negatively impacted by these interruptions. In response to these difficulties, this study proposes a novel method for traffic monitoring. By combining YOLOv5, optical flow, and recurrent neural networks (RNN) with image processing and artificial neural networks, a unified traffic monitoring system can be achieved. We went with YOLOv5 because of how well it identifies various automobiles. The number of vehicles is counted between video frames using Optical Flow, and then the traffic density is classified using RNN. With an accuracy of 87% following testing, RNN was clearly a winner when it came to vehicle density classification. The goals of this research are to lessen the societal and environmental toll of traffic congestion, increase our knowledge of and ability to control Jakarta's traffic, and lay the groundwork for the creation of more advanced traffic monitoring systems. The growing traffic issues in the nation's capital are anticipated to be alleviated with this strategy.
Development of Chatbot Services for Ordering Media Support Using Fuzzy Logic Algorithm: Case Study of PT. Pemuda Cari Cuan (Mangkokku) Aris Afriyanto Aris; Yohanes Eka Wibawa
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.2

Abstract

The importance of customer service in the modern business world cannot be ignored. Providing customers with good service can increase their satisfaction and strengthen the company's and customers' relationship. In the digital era, customer service increasingly shifts to online platforms, such as social media and instant messaging applications. However, providing efficient and responsive services on these platforms can take time and effort. At Mangkokku Restaurant, using social media platforms for promotions, discounts, and other information has become part of the business strategy. However, many customers need help understanding the context of the information in Mangkokku's social media posts. In addition, customers at dine-in outlets often repeat questions about promotions and discounts to the staff at the outlet, especially when the outlet is busy, and the staff needs help providing excellent and fast service. Therefore, research on chatbot services is considered a solution to overcome limitations in communication between staff and customers. With technological advances, chatbots are expected to provide positive benefits. This research uses a fuzzy logic algorithm to help chatbots find the expected response from customers. Apart from that, interviews with the marketing division, customer service, and outlet staff were conducted to collect data on questions and information that needed to be conveyed to customers. In this way, customers at Mangkokku Restaurant are expected to be able to quickly and efficiently ask about menus, promos, discounts, or other information via this chatbot service.
Climbing Information System Design Web-Based Mount Gede Pangrango Using the Waterfall Method Gilang Rizki Padilah; Gina Purnama Insany; Kamdan Kamdan
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.5

Abstract

Mountain climbing is a popular activity among the Indonesian community. In the current digital era, websites can serve as an effective platform to facilitate communication and collaboration among mountain climbers. This research aims to design and develop a website for the Indonesian mountain climbing community using PHP, HTML, and CSS programming languages, with a case study on Mount Gede Pangrango. The research methodology includes needs analysis, website design, and implementation. The waterfall method is employed in the system development, and testing is conducted using black box testing and usability methods. In the implementation phase, coding and page design are carried out according to the pre-established design, including color selection, typography, and layout settings. This research results in a website designed and built to facilitate climbers planning to ascend Mount Gede Pangrango. After several trials, the website received overwhelmingly positive responses from respondents, with an average rating of 90%. This result indicates that the website effectively assists users in obtaining information about climbing Mount Gede Pangrango.
Detection of Lung Cancer Malignancy Types on CT-Scan Using the Convolutional Neural Network Method at PHC Hospital Surabaya Kholilul Rohman Kurniawan; Endang Setyati; Francisca Haryanti Chandra
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.6

Abstract

There are many uses for digital image processing, ranging from tumor and cancer detection in the body to reading blood cells. The rate of lung cancer represents about 13.27% of the total cancer cases, and this shows that lung cancer is the main type of disease in men. Lung cancer is one of the most dangerous and life-threatening diseases in the world. In Indonesia, lung cancer is more often detected when patients are at an advanced stage. Therefore, in this paper, we applied Deep Learning to solve a lung cancer malignant detection system; it is used to detect and classify nodule areas. So that lung cancer detection can be obtained with accurate results. This paper explains the working system for detecting lung cancer malignancies using a Convolutional Neural Network (CNN) and the model architecture for training the dataset using the EfficientNet model. This study collected 800 lung CT images from PHC Surabaya Hospital in DICOM format. A total of 13 layers with EfficientNet architecture and classification layers for each type of cancer class have been used in the model. The experimental results of the model achieved satisfactory results with an accuracy of 99.46%, with a maximum epoch of 30 and a mini-batch size of 128.
Object Sorting Conveyor with Detection Color Using ESP-32 Camera Python Based on Open-CV Indah Sulistiyowati; Hafidz Maulana Ichsan; Izza Anshory
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.7

Abstract

The OpenCV Python library has been developed in all technology fields, including the industrial sector. In the industrial world, there are objects sorting tools in the form of conveyors. These instruments are presently more advanced since they employ cameras to read the things that should be sorted. The purpose of applying the Open Source Computer Vision Library (OpenCV) system to this object’s sorter conveyor is to make it easier to sort objects based on color detection technology. The OpenCV method for object detection based on color was employed to select those objects. The first step in identifying the object in question is to capture RGB (red, green, and blue) objects in real time and transform their colors into HSV. Additionally, by masking the object to be centered and applying a threshold, the morphological process can remove unnecessary noise from the image. The investigation results include the ability to differentiate objects based on RGB color when sorted by considering the HSV value on the surface of colored objects.
Decision-Making in Gripper Control Systems Using Fuzzy Logic Method and Telegram Application Richa Watiasih; Junior Risqy Cosabagus
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.8

Abstract

The application of the gripper in the industrial world has facilitated human work in the sorting process but has the disadvantage of not being able to sort objects based on the object's color. Conditions like these can affect the production quality factor when sorting objects. This research resulted in a gripper end effector system using the fuzzy method and the telegram application as a control, which has a function to distinguish the color of objects gripped by the gripper, thereby minimizing errors in sorting objects based on color. Telegram is used because the application is relatively light and can be accessed anywhere as long as it is connected to an internet connection. This study uses the fuzzy logic method as a decision-making process. The fuzzy method is used because it is very flexible and has a tolerance value in the existing data. The telegram function in this study is the main control to give orders to the gripper. The TCS3200 color sensor, in this study, is used to detect object color. The TCS3200 sensor converts the light intensity value to 8 bits so that the microcontroller can read it for each color in the test. The colors red, green, and blue were chosen as a reference because they are the primary or basic colors of all colors. From the results of testing the entire system in this study, 90% success was obtained in moving objects precisely based on the object's color. This result is enough to prove that the system can work properly.

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