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All Journal Jusikom : Jurnal Sistem Komputer Musirawas PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Martabe : Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Jurnal Software Engineering and Computational Intelligence Media Journal of General Computer Science (MJGCS)
Muhammad Sulkhan Nurfatih
Universitas Serelo Lahat
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Social Sciences

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Journal : Media Journal of General Computer Science (MJGCS)

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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.
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.
Co-Authors Agustian Prakarsyah Arief Zikry Darwin Kesuma, Darwin Deris Stiawan Eko Arip Winanto Firza Septian Heri Fitriadi Mohd Yazid Idris Rusilawati Kasisariah, Tri Uwi'ah, Mutata Yusi Nurmalasari