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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA CommIT (Communication & Information Technology) Al-Jabar : Jurnal Pendidikan Matematika Union: Jurnal Ilmiah Pendidikan Matematika Jurnal Matematika: MANTIK Wacana Akademika : Majalah Ilmiah Kependidikan Numeracy : Jurnal Ilmiah Pendidikan Matematika IndoMath: Indonesia Mathematics Education BAREKENG: Jurnal Ilmu Matematika dan Terapan Teorema: Teori dan Riset Matematika JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) Jurnal Inovasi Pendidikan dan Sains Jurnal Informatika Teknologi dan Sains (Jinteks) Pedagogik : Jurnal Pendidikan Guru Sekolah Dasar Recent in Engineering Science and Technology Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Applied Mathematics and Statistics
Samsul Arifin
Statistics Department, School Of Computer Science, Bina Nusantara University, Indonesia
Agriculture, Biological Sciences & Forestry Arts Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Predicting Citation Dynamics and Mapping Research Trends in Nanocellulose: A Bibliometric and Machine Learning Approach (2021–2025) Sijabat, Edwin Kristianto; Arifin, Samsul
JURNAL INOVASI PENDIDIKAN DAN SAINS Vol 6 No 3 (2025): December
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Nahdlatul Wathan Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51673/jips.v6i3.2709

Abstract

This study aims to map research trends and predict citation dynamics in nanocellulose research within the materials science domain during 2021–2025. A quantitative bibliometric approach was employed using metadata retrieved from the Scopus database, followed by network visualization with VOSviewer and advanced data analysis using Python and machine learning techniques. A total of 2,971 publications were analyzed to identify publication patterns, collaboration networks, thematic evolution, and citation behavior. The results show that China dominates publication output and funding, while key journals and authors form highly interconnected citation networks. Topic modeling reveals emerging research fronts in biomedical hydrogels, nanocomposite films, and sustainable processing. Citation prediction using regression-based machine learning achieved moderate performance (R² = 0.23), indicating potential for early impact estimation. This study concludes that integrating bibliometrics with machine learning provides a comprehensive and predictive perspective on the evolving landscape of nanocellulose research and can support strategic research planning and policy decisions
AI-AUGMENTED HEALTH INFORMATION SYSTEM DESIGN FOR SCALABLE MOBILE MENTAL WELLNESS SUPPORT IN INDONESIA Tiawan; Eliza Ariesta; Nilam Atsirina Krisnaputri; Amril Mutoi Siregar; Surjandy; Merios Gusan Putra; Dani Lukman Hakim; Samsul Arifin; Nur Dava Kurniawan
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 1 (2026): EDISI 27
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i1.6974

Abstract

Indonesia faces a youth mental health crisis, with limited access to professional care. WHO recommends one mental health worker per 30.000 people, but Indonesia only has 1:200.000 for general mental health personnel and 1:223.587 for psychiatrists. This paper addresses the implementation gap through the design and integration of an AI augmented health information system within Teman Curhat, a mobile mental wellness platform. We applied thematic analysis to expert interviews and used K-Means clustering on 16.689+ user reported cases to classify concerns into three severity levels. The system’s novelty lies in embedding on device Gemini AI for offline triage, ethical chatbot support, and adaptive user routing. Key outputs include a validated clustering model (Silhouette Score: 0.61), AI assisted classification logic, integration within Android Studio, and a scalable conversational interface. This innovation supports SDG 3 (Good Health and Well being) and SDG 10 (Reduced Inequalities) by enabling inclusive, responsive, and privacy focused digital mental health services for underserved communities.
MODEL CHATBOT AI AGENT BERBASIS CONVERSATIONAL AGENT UNTUK BISNIS DIGITAL LAPTOPCARE Tiawan; Eliza Ariesta; Nilam Atsirina Krisnaputri; Amril Mutoi Siregar; Surjandy; Merios Gusan Putra; Dani Lukman Hakim; Samsul Arifin; Muhammad Fathir Fahlevi; Favian Jarsi Taufiqqurakhman; Hexsel Aldoegasha; Alya Nabilah; Taufiqqurahman Hutri; Nur Davi Kurniawan
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 1 (2026): EDISI 27
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i1.6975

Abstract

Perkembangan teknologi Conversational Agent (CA) memungkinkan pengembangan chatbot berbasis kecerdasan buatan untuk mendukung layanan bisnis digital. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan chatbot AI Agent sebagai layanan dukungan pelanggan pada model bisnis perawatan laptop yang dikembangkan oleh mahasiswa. Metode yang digunakan adalah pendekatan Conversational Agent dengan integrasi n8n sebagai platform otomasi alur kerja, Telegram sebagai saluran komunikasi, Google Gemini Chat Model sebagai pemroses bahasa, serta Google Spreadsheet sebagai sumber data terstruktur untuk informasi produk dan layanan. Sistem chatbot dirancang sebagai agen berbasis tugas dengan aturan bisnis yang mengatur jenis pertanyaan dan layanan yang dapat diberikan. Hasil penelitian menunjukkan bahwa chatbot mampu memberikan respons yang akurat, kontekstual, dan konsisten terkait informasi layanan, stok barang, estimasi harga, serta kebutuhan pelanggan secara real-time. Implementasi ini membuktikan bahwa integrasi AI Agent dengan platform otomasi dan data terstruktur dapat meningkatkan efisiensi layanan pelanggan serta mendukung pengembangan model bisnis digital di bidang perawatan laptop.
PERANCANGAN FITUR DARURAT DAN PENGINGAT PADA APLIKASI JAMAAH UMROH XYZ MENGGUNAKAN SCRUMBAN Tiawan; Nusaibah; Rifky Kurniawan; Eliza Ariesta; Nilam Atsirina Krisnaputri; Amril Mutoi Siregar; Surjandy; Merios Gusan Putra; Dani Lukman Hakim; Samsul Arifin; Citra Nur Napiah
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 1 (2026): EDISI 27
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i1.7049

Abstract

The problem of Umrah pilgrims getting lost and losing personal belongings is still common, especially in high-density areas such as the Grand Mosque and the Prophet's Mosque, with more than 50 cases of missing pilgrims per day during the peak Umrah season. A survey of 50 pilgrims showed that 86% of respondents experienced location disorientation and 74% had lost or nearly lost personal belongings. This study aims to design emergency and reminder features in the XYZ Umrah Pilgrim Application to improve security and management of pilgrim activities. The development method used is Scrumban, a combination of the iterative and structured Scrum method with the Kanban method that emphasizes workflow visualization and task management execution. The emergency feature is designed using the Fused Location Provider to send pilgrim location coordinates in real-time with a detection time of less than 30 seconds, while the reminder feature helps manage luggage and prayer schedules through a notification system. Functional and performance testing results show a feature success rate above 90%. The conclusion of this study shows that the integration of emergency and reminder features in one Umrah application with the Scrumban approach is able to improve the security and comfort aspects of the congregation.
Co-Authors Abdillah, Abdul Azis Abdul Azis Abdillah Adi Adi Agus Sukandi Alfian Alfian Alya Nabilah Ariesta, Eliza Arif Rahman Hakim Arumella Surgandini Assagaf, Idrus Bobbi Rahman Citra Nur Napiah Dewi Yanti Liliana Dwi Anto, Septian Dwi Wijonarko Edistria, Ega Edwin K Sijabat Effendi, Melody Elita Putri, Rizky Favian Jarsi Taufiqqurakhman Ga, Jonri Lomi Hexsel Aldoegasha I Gusti Agung Anom Yudistira Indra Bayu Muktyas Indra Bayu Muktyas Jimy, Valensius Jonathan, Stanley Jufra, Arlita Aristianingsih Jufra, Jufra Klara Iswara Sukmawati kurniawan, Rifky Lucky, Henry Manurung , Monica Mayeni Manurung, Mika Meitriana Manurung, Monica Mayeni Muhamad Faisal, Muhamad Muhammad Amien Ibrahim Muhammad Faisal Muhammad Fathir Fahlevi Muktyas, Indra Bayu Muzakki, Zahran Nerru Pranuta Murnaka, Nerru Pranuta Nilam Atsirina Krisnaputri Nugraha, Edwin Setiawan Nur Dava Kurniawan Nur Davi Kurniawan Nusaibah Nusaibah Pimpi, La Pratama, Muhammad Nabil Priambodo, Oktanindita Puguh Wahyu Prasetyo, Puguh Raditha, Alya Maura Ramadhani, Sausan Repka, Joe Rezakusuma, Muhammad Rinda Nariswari Rinda Nariswari RONI Rully Charitas Indra Prahmana Rusli P. D. Kolnel Safitri, Raudhatun Seleki, Jacob Stevy Setyawan, Fariz Siregar, Amril Mutoi Siti A. M. Karubaba Suharno Suharno Sulistiawati Sulistiawati Sulistiawati Sulistiawati Surjandy Susyanto, Nanang Sutrisno, Utis Taufiqqurahman Hutri Tiawan Tri Handayani Usep Widyakusuma, Nita Wijaya, Andryan Kalmer Wijayanti, Dian Eka Winarto Selamet, Muhammad Windria, Hening Wiwik Wiyanti, Wiwik Yanuar Yanuar Yulia Wulandari, Yulia Zenklinov, Amanatullah Pandu