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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Ulul Albab: Jurnal Studi Islam MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Prosiding Seminas Competitive Advantage Prosiding SNATIKA Vol 01 (2011) Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Applied Information System and Management Letters in Information Technology Education (LITE) Journal of Applied Data Sciences Science in Information Technology Letters International Journal of Engineering, Science and Information Technology Bulletin of Social Informatics Theory and Application Jurnal ilmiah teknologi informasi Asia
Fachrul Kurniawan
Universitas Islam Negeri Malang
Religion Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Systematic Literature Review: Application of Interactive Educational Games ‘Climate Change and Mitigation Effort’ Hadi, Muhammad Aulia Syamsul; Kurniawan, Fachrul
Telematika Vol 22 No 3 (2025): Edisi Oktober 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i3.14092

Abstract

The purpose of this Systematic Literature Review (SLR) is to explore the role of interactive educational games in increasing public awareness about climate change and the mitigation strategies that can be adopted. The review examines how educational games can enhance understanding of climate change by integrating narratives, simulations, and gamification. A systematic approach was used to collect and analyze 28 relevant academic papers, focusing on interactive games used to teach climate change. The methodology involved identifying studies from various databases, applying specific inclusion and exclusion criteria, and synthesizing findings from studies that explore the effectiveness of games in environmental education.The review found that interactive educational games, especially those utilizing augmented reality (AR), simulation, and narrative-based approaches, are effective tools for raising awareness about climate change. These games engage players by simulating real-world environmental challenges and offering mitigation solutions. However, the effectiveness varies depending on the audience's age, background, and technical skills. Challenges such as limited access to technology and differing levels of engagement across age groups were identified, but these can be addressed by using more accessible mobile platforms and gamified learning experiences. This SLR contributes to the understanding of how interactive games can be a valuable tool in climate change education. It highlights the potential of combining emerging technologies like AR and machine learning with traditional educational methods to create engaging and effective learning experiences. The paper provides insights into the current state of research on game-based climate change education. 
A hybrid GoogLeNet–GLCM feature extraction framework for textural representation of post-disaster building damage imagery Amani, Holidiyatul; Almais, Agung Teguh Wibowo; Abidin, Zainal; Nugroho, Fresy; Kurniawan, Fachrul; Sugiharto , Tomy Ivan
Jurnal Ilmiah Teknologi Informasi Asia Vol 20 No 1 (2026): Volume 20 Issue 1 2026 (8)
Publisher : LP2M Institut Teknologi dan Bisnis ASIA Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v20i1.1214

Abstract

Accurate representation of visual characteristics in post-disaster building imagery is crucial for downstream analytical tasks such as damage interpretation, retrieval, and automated assessment. This study presents a focused investigation of feature extraction using a hybrid approach that integrates deep semantic representations from the GoogLeNet architecture with statistical texture descriptors inspired by the Gray-Level Co-Occurrence Matrix (GLCM). The objective of this work is limited strictly to the generation and analysis of semantic–textural feature vectors rather than the development or evaluation of any classification or prediction model. High-level feature maps are obtained from a selected convolutional layer of GoogLeNet, after which statistical texture properties—contrast, energy, and homogeneity—are computed per channel. A representative set of feature channels is analyzed to demonstrate the capabilities of the proposed hybrid extraction pipeline. The results demonstrate the potential of semantic–textural descriptors to provide interpretable feature characteristics in building-damage imagery. This study provides a methodological foundation and analytical insight for future works that may incorporate these feature representations into classification, clustering, or decision-support frameworks.
Co-Authors ., Rahmadwati Aang Subiyakto Abd. Rahman Ahlan Ady Wicaksono Agung Teguh Wibowo Almais Aji Prasetya Wibawa Ajib Hanani Albas, Juan Alfachruddin, M. Nabil Fahd Amani, Holidiyatul Andri Pranolo Anusua Ghosh, Anusua Artanti, Vera Ashar, Muhammad Asrul Sani Atmaja, I Made Ari Dwi Suta Azmi, Agus N Balogun, Naeem A Camargo, Jair Cengiz, Korhan Dwi Yuniarto Fachry Khusaini Fresy Nugroho Gianto Widodo Hadi, Muhammad Aulia Syamsul Hani Nurhayati Hartawan, Muhammad S Hoz, César De La Huda, Muhammad Q I Nyoman Gede Arya Astawa Ikhlayel, Mohammed Ilmi, Rifqy Rosdiyah Kadir, Nurchaerani Karisma, Alfiana Intan Kurubacak, Gulsun Laili, Ufil Hidayatul Leonel Hernandez, Leonel Lokapitasari Belluano, Poetri Lestari M. Faisal Mubdik, M. Ahsanul Muhammad Faisal Muji, Muji Nashrul Hakiem Nia, Nur Jazilah Purnomo Budi Santoso Qurrohman, Taufiq Ridho, Faiz Mohammad Ririen Kusumawati Siti Helmyati Sri Harini Sugiharto , Tomy Ivan Sunu Jatmika, Sunu Supriyono Supriyono Suryatno, Agung Suseno, Hendra B Suyono Suyono Syaad Patmanthara Triyo Supriyatno Viva Arifin Voliansky, Roman W, Delliana Eka Wahyu Setiawan Yunifa Miftachul Arif Zainal Abidin