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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 420 Documents
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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): June
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.
Comparative Study of Obesity Levels Classification Syahrazad Syaukat Al Malaky; Alisya Akbar Choirun Nisa; Siti Armiyanti; Rizky Syahputra Setyawan
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 1 (2025): June
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i1.8

Abstract

Obesity is a growing global health problem, requiring accurate data analysis to understand and address contributing factors. The level of obesity can be identified based on eating habits and physical conditions, which consist of several parameters. However, the performance of widely used machine learning methods has not provided satisfactory results. Therefore, this study analyzes obesity data using pre-processing methods to improve data quality before classifying data. The dataset used is 2111 data and includes 17 variables/features. The classification methods are Random Forest Classifier, Light Gradient Boosting Machine (LGBM) Classifier, Decision Tree Classifier, and Extra Tree Classifier. The process of data pre-processing involves data integration, data labeling, data transformation, normalization, and data cleansing. After pre-processing the data, four algorithms were used to identify patterns in the obesity data. The Random Forest Classifier is used for its ability to handle unbalanced data and reduce the risk of overfitting. The LGBM Classifier is used for a probabilistic approach to classification. The Decision Tree Classifier is applied for straightforward interpretation and clear understanding of patterns, while the Extra Tree Classifier is applied to improve the variety and accuracy of classification. The experimental results showed that a good data pre-processing method significantly improved the performance of the classification. Among the four algorithms tested, the Random Forest Classifier and Extra Tree Classifier performed best in accuracy and generalizability. Combining appropriate data pre-processing with powerful classification algorithms can provide deep insights to address obesity problems and formulate effective public health interventions.
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): June
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): June
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): June
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): June
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): June
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): June
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.
Implementation of Data Mining Algorithm C4.5 to Predict Loan Payments in the Harum Manis Women's Union in Sirnoboyo Village Miftahul Mukti Anas
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 1 (2024): June
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i1.10

Abstract

The women's union, "Harum Manis" is an active savings and loan cooperative that uses members' funds in savings and loans. Given the large number of prospective members who register each year, the union still needs to be more selective in accepting prospective members who only see from work and salary, thus causing lousy credit. To reduce the occurrence of bad loans, predicting prospective members' smooth payment status and finding prospective members, including bad credit or current loans, is necessary. This research applies classification data mining techniques using the Decision Tree C4.5 method to determine the smooth payment class, which is a jam class or a smooth class. The attributes used in this study consist of four variables, namely age, marital status, income, and home status. System testing is done three times testing. The data were taken from 102 data for the "Harum Manis" Women's Union Member Loan data. Based on the test results, it was found that the first test produced the highest accuracy, reaching 64%.
Copper Winding Voice Coil Speaker Microcontroller Based Adi Kurniawan Saputro; Hanifudin Sukri; Andre Putra Pratama; Koko Joni; Achmad Fiqhi Ibadillah; Monika Faswia Fahmi
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 2 (2024): December
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i2.1

Abstract

The voice coil is a vital speaker component, producing sound through electromagnetic vibrations. Generally, commercially available voice coils do not meet standard quality specifications, especially in terms of copper quality and adhesive strength. This problem often leads to issues such as coil burning or breakage during operation. On the other hand, ordering custom voice coils through manual winding processes requires considerable time. This study aims to address these limitations by designing an automated coil winding device that employs Pulse Width Modulation (PWM) techniques to control the speed of a DC motor, enabling the production of voice coils with specifications and durability tailored to specific needs. An Arduino Nano microcontroller controls the system and consists of a BTS 7960 motor driver, a Direct Current (DC) motor, an optocoupler sensor, a rotary encoder, a 4x4 keypad, and an LCD display with an I2C interface. Coil durability testing was conducted using an ohmmeter and an amplifier with a transformer ranging from 20A 45V to 30A 45V. The testing results indicate that coils produced with the automated winder can be adjusted to approach the 8-ohm specification, with a tolerance of 0.1 to 0.3 ohms, suitable for speaker requirements. The comparison results show that commercial voice coils exhibit resistances below 8 ohms, with the lowest resistance measured at 4.9 ohms for larger coils. During power testing, coils with a diameter of 35.5 mm and copper wire diameters of 0.20 mm and 0.23 mm broke when tested with a 20A 45V amplifier. In contrast, commercial coils remained stable up to an input power of 372 W and output power of 273 W, although a burning odor was detected. These findings indicate that the copper quality in commercial coils is superior in resisting amplifier power up to 30A 45V compared to coils produced with the automated device.

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