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All Journal Jurnal Teknik Industri Jurnal Keuangan dan Perbankan Trikonomika: Jurnal Ekonomi Indonesian Journal of Science and Technology Jurnal Ilmiah Econosains Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Bisnis dan Manajemen YUME : Journal of Management JURISMA: Jurnal Riset Bisnis & Manajemen Majalah Ilmiah UNIKOM FIRM: Journal of Management Studies Indonesian Community Service and Empowerment Journal (IComSE) International Journal of Research and Applied Technology (INJURATECH) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Journal of Artificial Intelligence and Digital Business Journal Research of Social Science, Economics, and Management Eduvest - Journal of Universal Studies Jurnal Ilmiah Bisnis dan Ekonomi Asia (Jibeka) Jurnal Salingka Nagari ASEAN Journal for Science and Engineering in Materials ASEAN Journal of Educational Research and Technology Jurnal Manajemen, Bisnis dan Kewirausahaan
Eddy Soeryanto Soegoto
Program Studi Manajemen, Fakultas Ekonomi Dan Bisnis, Universitas Komputer Indonesia
Aerospace Engineering Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Neuroscience Social Sciences Other

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Energy-Harvesting Materials for Autonomous Smart Farming Sensors: A Literature Review Septiani, Riska Endah; Kurniawan, Bobi; Luckyardi, Senny; Soegoto, Eddy Soeryanto; Ximmataliyev, Dostnazar; Yusof, Mohd. Kamir; Chochole, Tomas; Zangana, Hewa Majeed
ASEAN Journal for Science and Engineering in Materials Vol 6, No 1 (2027): (ONLINE FIRST) AJSEM: Volume 6, Issue 1, March 2027
Publisher : Bumi Publikasi Nusantara

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Abstract

The integration of the Internet of Things (IoT) in smart farming is hindered by limited battery life and the environmental impact of electronic waste. This review evaluates the development of energy-harvesting materials as a solution to power autonomous agricultural sensors. Through a systematic review, this paper analyzes three main mechanisms: Organic Photovoltaic (OPV), triboelectric nanogenerator/piezoelectric nanogenerator (TENG/PENG), and thermoelectric generator (TEG). Flexible polymers for TENGs and perovskite-based solar cells have the highest potential in addressing canopy shading and outdoor weather challenges. However, material toxicity and degradation due to UV and humidity remain major obstacles. Future research must prioritize biocompatible materials and hybrid systems to ensure the sustainability of precision agriculture.
Predictive Modelling of Electronic Materials: A Review of Deep Learning Techniques in Computer Engineering Rafdhi, Agis Abhi; Maulana, Hanhan; Luckyardi, Senny; Soegoto, Eddy Soeryanto; Ximmataliyev, Dostnazar; Wen, Goh Kang; Chochole, Tomáš; Zangana, Hewa Majeed
ASEAN Journal for Science and Engineering in Materials Vol 5, No 3 (2026): (ONLINE FIRST) AJSEM: Volume 5, Issue 3, December 2026
Publisher : Bumi Publikasi Nusantara

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Abstract

This review evaluates the application of deep learning (DL) for the predictive modeling of electronic materials in computer engineering. We analyzed peer-reviewed literature across four major databases, focusing exclusively on advanced architectures like Graph Neural Networks (GNNs) and Generative models. Results indicate these models accurately predict critical properties, such as band gaps and thermal conductivity, for next-generation semiconductors, 2D materials, and memristors. These high accuracies are achieved because architectures like GNNs effectively capture complex 3D spatial interactions without requiring manual feature engineering. However, practical fabrication remains hindered by data scarcity, algorithmic opacity, and a profound "Sim-to-Real Gap". While DL accelerates predictive design, sustaining Moore's Law ultimately requires developing autonomous "Self-Driving Labs" and Large Material Models to bridge digital predictions with physical synthesis.
Co-Authors Adam Mukharil Bachtiar Adani Ghina Puspita Sari Adhea Vinora Putri Adilah, N Agis Abdi Rafdhi Agis Abhi Rafdhi Agung Nugraha Agus Mulyana Agustin, Nada Delia Akbar, Aldi Mohamad Albar, Chepi Nur Asep Bayu Dani Nandiyanto Asep Koswara Bachtiar, Adam Mukharil Bobi Kurniawan, Bobi Burhanuddin Burhanuddin Chepi Nur Albar Chochole, Tomas Cindy Nuke Mardika Daniel Maruli Dedi Sulistiyo Soegoto Dharmayanti, Dian Dicky Kurniawan Dina Oktafiani Elfiyah, E Fadillah, Ismail Hudan Firmansyah Firmansyah Fitri Febriyanti Fristaloka, Gina Dwi Hayati, Euis Neni Hayin Ananta Herman Soegoto Herry Saputra Ilham Zaki Iluh Sri Purwani Irine Sofianty Jumansyah, Rizky Kamil, N H Karin, Juliana Lia Warlina Luckyardi, Senny Lukito Angga Prasakti M Mulyanto Makalalag, Sukiman Maryati, Mari Maulana, Hanhan Mohamad Akbar, Aldi Muhammad Ananta Hafidz Muhammad Habibi Putera Muhammad Ikhlas Naufalsyah Ranau Muhammad Irfan Nada Archy Dhafina Nadia Tahiyyah Alifia Natalia, Tri Widiati Novia Aenu Rizqi Nurintang Nurintang Nurul Amelia Puri Swastika Gusti Krisna Dewi Putera, Muhammad Habibi Rafdhi, Agis Abhi Ragadhita, Risti Rahma Wahdiniwaty Rahma Wahdiniwaty Rahmadani, Indri Kristanty Raka Pradana Kostarian Rania Febiananda Rina Maryanti Rizky Jumansyah Rofi Fadilah Madani Saputra, Herry Senny Luckyardi Septiani, Riska Endah Shinta Wanda Kusuma Modjo Soegoto, Dedi Sulistiyo Sri Supatmi Sri Supatmi Sri Yuliawati Sugilar, Audya Pridita Sugiyono, Imanuel Eko Anggun Sumitra, Irfan Dwiguna Suryatno Wiganepdo Soegoto Sutisnawati, Yayah Tarso, Tarso Theresia Valentina Lumban Gaol Tiara Salsabila Tri Widianti Natalia Wellga Berlianti Wen, Goh Kang Ximmataliyev, Dostnazar Yusof, Mohd. Kamir Zangana, Hewa Majeed Zanjabil Zulkarnain