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All Journal Journal of Intelligent Networks and IoT Global Media Journal of General Computer Science (MJGCS)
Cahyadi, Hartanto Dwi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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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.
Desain dan Implementasi Prototipe Robot Pembersih Sampah di Sungai Berbasis Raspberry Pi 4 Model B Cahyadi, Hartanto Dwi; Fajri, Ricky Maulana; Setiawan, Candra; Akbar Deazwara, Muhammad Rizki
Journal Of Intelligent Networks and IoT Global Vol 3 No 2 (2025)
Publisher : Universitas Indo Global Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jinig.v3i2.6653

Abstract

Sungai Musi menghadapi ancaman polusi plastik yang serius, yang merusak ekosistem dan memicu banjir akibat penyumbatan aliran air. Penelitian ini bertujuan untuk merancang prototipe robot pembersih sampah semi-otomatis menggunakan Raspberry Pi 4 Model B sebagai pusat kendali. Sistem ini mengintegrasikan visi komputer menggunakan algoritma YOLO (You Only Look Once) untuk deteksi sampah plastik secara real-time. Robot dirancang dengan struktur katamaran menggunakan material styrofoam dan triplek untuk stabilitas maksimal di atas air. Metodologi penelitian mencakup perancangan perangkat keras, pengembangan perangkat lunak berbasis Python, dan pengujian lapangan. Hasil pengujian menunjukkan bahwa sistem mampu mendeteksi botol plastik dengan tingkat kepercayaan hingga 87% pada jarak 100 cm, sementara pengujian jarak optimal untuk stabilitas deteksi berada pada rentang 30–90 cm. Meskipun terdapat kendala mekanis pada sinkronisasi motor, prototipe ini membuktikan efektivitas penggunaan Raspberry Pi dan AI dalam upaya pelestarian lingkungan sungai secara semi-otomatis.
Co-Authors Akbar Deazwara, Muhammad Rizki Candra Setiawan Ferdiansyah Muhammad Gald Teary Ricky Maulana Fajri Tasmi