cover
Contact Name
Eko Arip Winanto
Contact Email
ekoaripwinanto@gmail.com
Phone
+6281367704735
Journal Mail Official
mjgcs@mase.or.id
Editorial Address
Contact Jl. R. Wijaya Lorong Akimar No.271, The Hok, Kec. Jambi Sel., Kota Jambi, Jambi 36138
Location
Kota jambi,
Jambi
INDONESIA
Media Journal of General Computer Science (MJGCS)
ISSN : -     EISSN : 30313651     DOI : https://doi.org/10.62205/mjgcs.v1i2.21
Media Journal of General Computer Science (MJGCS), e-ISSN: 3031-3651 is a peer-reviewed journal in Indonesian or English. The purpose of this publication is to disseminate high-quality articles that are devoted to discussing any and all elements of the most recent and noteworthy advancements in the field of computer science. The applications of information technology, applied computing, and computer science are all included in its purview. Skip to main contentSkip to main navigation menuSkip to site footer Open Menu Home / Aims and Scope Aims and Scope Computer Science: Computer Architecture, Parallel and Distributed Computing, Pervasive Computing, Computer Networks, Embedded Systems, Human-Computer Interaction, Virtual/Augmented Reality, Computer Security, Software Engineering (covering Software Lifecycle, Management, Engineering Process, and Engineering Tools and Methods), Programming (encompassing Programming Methodology and Paradigm), and Data Engineering (involving Data and Knowledge Level Modeling, Information Management, Knowledge-Based Management Systems, and Knowledge Discovery in Data). This diverse landscape also includes Network Traffic Modeling, Performance Modeling, Dependable Computing, High-Performance Computing, Human-Machine Interface, Stochastic Systems, Information Theory, Intelligent Systems, IT Governance, Networking Technology, Optical Communication Technology, Next Generation Media, Robotic Instrumentation, Information Search Engine, Multimedia Security, Computer Vision, Information Retrieval, Distributed Computing Systems, Mobile Processing, Next-Generation Networks, Computer Network Security, Natural Language Processing, Business Process, and Cognitive Systems. Information Systems : Data Engineering (comprising Data and Knowledge Level Modeling, Information Management, Knowledge-Based Management Systems, and Knowledge Discovery in Data), Software Engineering (addressing Software Lifecycle, Management, Engineering Process, and Engineering Tools and Methods), Information Retrieval, IT Governance, Networking Technology, Business Process, Intelligent Systems, Multimedia Security, Information Search Engine, Distributed Computing Systems, Mobile Processing, Next-Generation Networks, Computer Network Security, Natural Language Processing, and Cognitive Systems. Signal Processing : Signal Theory, Digital Signal and Data Processing, Stochastic Processes, Detection and Estimation, Spectral Analysis, Filtering, Signal Processing Systems, Environmental Signal Processing, and various applications such as Image Processing, Pattern Recognition, Optical Signal Processing, Multi-dimensional Signal Processing, Communication Signal Processing, Biomedical Signal Processing, Geophysical and Astrophysical Signal Processing, Earth Resources Signal Processing, Acoustic and Vibration Signal Processing, Data Processing, Remote Sensing, Speech Processing, Signal Processing for Audio, Visual, and Performance Arts, Radar Signal Processing, Sonar Signal Processing, Seismic Signal Processing, Medical Imaging Equipment and Techniques, Biomedical Imaging and Image Processing, Video Processing, Industrial Applications, and New Applications. Telecommunication: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platforms, Communication Network and Systems, and Telematics Services and Security Network. Instrumentation & Control: Optimal, Robust, and Adaptive Controls, Nonlinear and Stochastic Controls, Modeling and Identification, Robotics, Image-Based Control, Hybrid and Switching Control, Process Optimization and Scheduling, Control and Intelligent Systems, Artificial Intelligence and Expert Systems, Fuzzy Logic, and Neural Networks, and Complex Adaptive Systems.
Articles 5 Documents
Search results for , issue "Vol. 1 No. 2 (2024): MJGCS" : 5 Documents clear
Development of Smart Blind Stick using Global Positioning System Yamuna Mahadevan; Siti Haryanti Hairol Anuar
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.21

Abstract

The smart blind stick using Global Positioning System (GPS) is an assistive device designed to enhance the mobility and independence of visually impaired individuals. Traditional blind sticks provide basic obstacle detection and aid in navigation, but it lacks an advanced feature for precise location tracking and route guidance. This project aims to leverage GPS technology by developing a prototype of smart blind stick that can send information to the user's position and provide audio-based for alert. The proposed system incorporates a GPS module to acquire real-time coordinates and a microcontroller to process the data. The device is designed to be lightweight, portable, and user-friendly. The software component involves developing a user interface that allows the user to input their destination or select pre-defined routes. The system then calculates the optimal path based on the GPS coordinates and provides step-by-step directions, that include distance and directional cues. To enhance the functionality, additional features of obstacle detection using ultrasonic sensors have been integrated. These sensors can alert the user about potential obstacles in them path, further improving safety during navigation. The smart blind stick using GPS aims to offer a cost-effective and efficient solution for visually impaired individuals, enabling them to navigate unfamiliar environments with confidence. The success of this project will be evaluated through simple user testing and feedback collection.
Identification of Indonesian Sign Language System Using Deep Learning in Yolo-based Arahmad taupiq; Muhammad Wildan Fajri; Dannylee
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.22

Abstract

Deafness, or hearing impairment, refers to the loss of auditory capability in one or both ears. Deaf communities often develop sign languages to facilitate communication. Sign language, which employs hand movements, is commonly adopted by individuals with hearing impairments. In Indonesia, two primary sign languages are used: BISINDO (Bahasa Isyarat Indonesia) and SIBI (Sistem Isyarat Bahasa Indonesia). The main distinction between these languages is that BISINDO employs both hands for signing, whereas SIBI uses only one hand. Individuals with hearing impairments face significant communication challenges. This study focuses on the detection of alphabets in the Indonesian Sign Language System (SIBI) using YOLO v5. The objective is to recognize alphabetic characters through hand gesture signals. Experimental results indicate a detection success rate of 95.38%, accurately identifying 23 out of the 24 tested letters.
Analysis of Accreditation's Impact on Student Numbers in South Sumatra Private Universities Using K-Means Clustering Muhammad Sulkhan Nurfatih; Yusi Nurmalasari; Agustian Prakarsyah
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.23

Abstract

Private universities in Indonesia are essential in meeting the educational needs of the country's increasing number of students. Among the key determinants of student enrollment is the accreditation status of these institutions. This study investigates how accreditation status influences student numbers at private universities in South Sumatra, employing the K-Means clustering method for analysis. Data from various institutions across South Sumatra were collected and analyzed, revealing distinct patterns in how universities are grouped based on their accreditation and enrollment figures. The findings shed light on the significant relationship between accreditation status and student enrollment, offering valuable insights for policymakers and university administrators. These insights can inform the development of effective student admission strategies, ultimately contributing to the growth and success of private universities in the region. This research not only highlights the importance of accreditation but also provides a comprehensive understanding of the factors driving student growth at private universities in South Sumatra.
Detection of Hoax News Using TF-IDF Vectorizer and Multinomial Naïve Bayes and Passive Aggressive Rizky Adrian; Musaddam; Muhammad Ikhsan; M. Riza Pahlevi. B
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.24

Abstract

The website is a source of information, but not all information is guaranteed to be correct. Some news can beconsidered hoaxes or not based on facts. This research aims to build a hoax news detection system on English languagenews websites. The method used involves the multinomial Naive Bayes and Passive Aggressive approaches.Classification report analysis shows the superiority of the Passive Aggressive Classifier with significant improvementsin all evaluation metrics compared to Multinomial Naïve Bayes. The conclusion is based on the characteristics of thedataset, confirming the effectiveness of the Passive Aggressive Classifier in solving the task of classifying fake news inEnglish, with the highest accuracy reaching 93.74%.
Vehicle Police Number Detection Using Yolov8 Gilang Ramadhan; Revinda Dwi Artanti Khairiyah; Salwa Natania; Abdul Harris
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.25

Abstract

This research discusses the application of the YOLOv8 object detection model in recognizing and extracting vehicle license plate numbers from vehicle images. This method leverages deep learning technology to achieve accurate and efficient detection of license plates under various visual conditions. The proposed approach utilizes deep neural networks to identify and extract license plate information with high precision. Experiments and evaluations were conducted using a diverse vehicle dataset, demonstrating YOLOv8's capability to detect license plates quickly and reliably. The experimental results show a promising accuracy level, highlighting the significant potential of this approach for vehicle license plate detection applications. The achieved accuracy rate is 90%.

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