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 25 Documents
Assessing Digital Literacy of Batanghari University Students: A Four-Pillar KOMINFO Framework Analysis Megawati Ananda Putri; Agustin, Imelda; Tiadef, Agra; Dwisura T, Ariaga; Maghfud, Sahal; Putra, Wahyudi Eka; Arsa, Daniel; Sutoyo, Mochammad Arief Hermawan
Media Journal of General Computer Science Vol. 3 No. 1 (2026): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v3i1.106

Abstract

The Society 5.0 era demands comprehensive digital literacy skills encompassing technical competencies, critical thinking, digital ethics, and active participation in digital spaces. This study assesses digital literacy levels of university students at Batanghari University, Jambi Province, using the four-pillar framework developed by the Ministry of Communication and Information Technology, Digital Literacy Activist Network, and Siberkreasi. The research employed quantitative descriptive approach with 100 students from 20 study programs aged 18-29 years. Data was collected through structured questionnaire containing 31 items measuring digital skills, digital safety, digital ethics, and digital culture using 4-point Likert scale. The instrument demonstrated high validity with correlation values above 0.361 and excellent reliability with Cronbach's Alpha of 0.95926. Findings reveal excellent overall digital literacy levels, with 1279 points in "Very High" category and 1034 points in "High" category. Digital Skills showed best performance, followed by Digital Culture, Digital Safety, and Digital Ethics. Results indicate student readiness for Society 5.0 era despite regional internet penetration below national average.
Analysis Of An Automatic Iot- Based Chili Plant Watering System Using Fuzzy Logic And The Adaline Algorithm Andani, Seli Puri; RAHMAD HIDAYAT LENDRIAN; Wati , Sinta; Jackson
Media Journal of General Computer Science Vol. 3 No. 1 (2026): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v3i1.117

Abstract

Chili plants are high-value horticultural commodities whose growth and productivity are strongly influenced by water availability. Inaccurate irrigation practices can reduce crop yield and lead to inefficient water usage. This study proposes an automatic chili plant watering system based on the Internet of Things (IoT) that integrates soil moisture sensors, the Adaptive Linear Neuron (ADALINE) algorithm for sensor data validation, and fuzzy logic for irrigation decision-making. The system is developed using a NodeMCU microcontroller and is equipped with a web-based interface for real-time monitoring. Experimental results show that the proposed system is capable of classifying soil moisture levels into appropriate irrigation categories and automatically activating the water pump according to actual field conditions. Repeated tests conducted at different times demonstrate consistent and stable system performance. Therefore, the proposed system effectively improves irrigation accuracy, enhances water-use efficiency, and facilitates remote monitoring of chili plant conditions.
IoT-Based Fire Detection System Using ESP32 and Telegram Cahyadi, Hartanto Dwi; Tasmi; Muhammad Gald Teary; Ferdiansyah
Media Journal of General Computer Science Vol. 3 No. 1 (2026): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v3i1.146

Abstract

The increasing adoption of artificial intelligence (AI) in educational technology has created new opportunities to support second language (L2) writing development. Beginner English learners often struggle with grammatical accuracy, limited vocabulary, and unclear sentence construction, while immediate and individualized feedback remains difficult to provide in traditional learning settings. This study proposes a rule-based AI writing assistant designed to deliver automated, transparent, and interpretable feedback for beginner-level English writing without relying on data-intensive machine learning models. The system employs symbolic AI principles through predefined grammatical rules and heuristic textual metrics to evaluate writing quality across three dimensions: grammar accuracy, vocabulary richness, and text clarity. Grammar errors are detected using regular expression-based rules, vocabulary quality is measured via lexical diversity ratios, and clarity is estimated using a length-based heuristic. These metrics are normalized and combined to produce an overall writing quality score. To enhance usability and learner engagement, the system integrates visual feedback elements, including progress bars, graphical score representations, and animated character responses. Functional testing using sample beginner texts demonstrates that the proposed system effectively identifies common writing issues, provides consistent scoring, and delivers immediate, explainable feedback. The results indicate that rule-based AI, when combined with visual feedback mechanisms, can offer a lightweight, efficient, and pedagogically meaningful solution for beginner English writing support. This approach is particularly suitable for educational contexts that prioritize explainability, accessibility, and low computational requirements.
A Rule-Based AI Writing Assistant for Beginner English Learners with Visual Feedback Zikry, Arief; Sari, Yusi Nurmala; Nurfatih, Muhammad Sulkhan; Septian, Firza
Media Journal of General Computer Science Vol. 3 No. 1 (2026): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v3i1.149

Abstract

The increasing adoption of artificial intelligence (AI) in educational technology has created new opportunities to support second language (L2) writing development. Beginner English learners often struggle with grammatical accuracy, limited vocabulary, and unclear sentence construction, while immediate and individualized feedback remains difficult to provide in traditional learning settings. This study proposes a rule-based AI writing assistant designed to deliver automated, transparent, and interpretable feedback for beginner-level English writing without relying on data-intensive machine learning models. The system employs symbolic AI principles through predefined grammatical rules and heuristic textual metrics to evaluate writing quality across three dimensions: grammar accuracy, vocabulary richness, and text clarity. Grammar errors are detected using regular expression-based rules, vocabulary quality is measured via lexical diversity ratios, and clarity is estimated using a length-based heuristic. These metrics are normalized and combined to produce an overall writing quality score. To enhance usability and learner engagement, the system integrates visual feedback elements, including progress bars, graphical score representations, and animated character responses. Functional testing using sample beginner texts demonstrates that the proposed system effectively identifies common writing issues, provides consistent scoring, and delivers immediate, explainable feedback. The results indicate that rule-based AI, when combined with visual feedback mechanisms, can offer a lightweight, efficient, and pedagogically meaningful solution for beginner English writing support. This approach is particularly suitable for educational contexts that prioritize explainability, accessibility, and low computational requirements.
An EUCS-Based Analysis of Student Satisfaction with ShopeePay Ningsih, Egi E.; Irawan, Beni; Gusriyanti, Dwi A.; Amroni
Media Journal of General Computer Science Vol. 3 No. 1 (2026): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v3i1.153

Abstract

ShopeePay is one of the digital wallet services widely used in online and offline transactions, especially among students. As part of the Shopee ecosystem, ShopeePay is expected to provide convenient, accurate, and satisfying services for its users. However, several limitations, such as the absence of cash withdrawal features, virtual debit cards, and investment services, may affect user satisfaction. These issues indicate the need for an evaluation of ShopeePay from the perspective of end users. This study aims to analyze the factors that influence user satisfaction with the ShopeePay application using the End User Computing Satisfaction (EUCS) model. The research adopts a quantitative approach by distributing questionnaires to students of Universitas Dinamika Bangsa (UNAMA) who actively use ShopeePay. The EUCS variables examined include Content, Accuracy, Format, Ease of Use, and Timeliness. Data analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS software and bootstrapping techniques. The results show that three variables significantly affect user satisfaction, while two variables do not. Among all variables, Format has the strongest influence on user satisfaction, highlighting the importance of interface design and information presentation.

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