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All Journal Faktor Exacta Jurnal Informatika Teknologi dan Sains (Jinteks)
Amril Mutoi Siregar
Institut Teknologi Sains Bandung
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Ketahanan Pembelajaran Mesin terhadap Adversarial examples: Metodologi dan Pertahanan Ade Kurniawan; Ely Aprilia; Achmad Indra Aulia; Amril Mutoi Siregar; Leonard Goeirmanto
Faktor Exacta Vol 18, No 2 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i2.26078

Abstract

This paper examines the vulnerability of machine learning models to adversarial examples: inputs that are subtly manipulated to deceive a model into making incorrect predictions. Although deep learning has demonstrated remarkable performance across various tasks, the security of these models remains a significant challenge. This study provides a comprehensive review of various methods for generating adversarial examples, a classification of attack techniques, and corresponding defense strategies, including both active and passive approaches. The findings indicate that a combination of several defense techniques is significantly more effective in enhancing model robustness compared to any single approach. This research is expected to provide a foundation for the development of more secure and reliable machine learning models for critical applications.
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 Achmad Indra Aulia Ade Kurniawan Alya Nabilah Citra Nur Napiah Dani Lukman Hakim Eliza Ariesta Ely Aprilia Favian Jarsi Taufiqqurakhman Hexsel Aldoegasha Leonard Goeirmanto Merios Gusan Putra Muhammad Fathir Fahlevi Nilam Atsirina Krisnaputri Nur Dava Kurniawan Nur Davi Kurniawan Nusaibah Rifky Kurniawan Samsul Arifin Surjandy Taufiqqurahman Hutri Tiawan