Article Per Year (5 Year)
p-Index From 2021 - 2026
4.541
P-Index
This Author published in this journals
All Journal The Asian Journal of Technology Management (AJTM) Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi TIJAB (The International Journal of Applied Business) Journal of Information Technology and Computer Engineering Building of Informatics, Technology and Science Buletin Ilmiah Sarjana Teknik Elektro International Journal of Artificial Intelligence and Robotics (IJAIR) International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) International Journal of Research and Applied Technology (INJURATECH) Sistem Pendukung Keputusan dengan Aplikasi Indonesian Journal of Education and Social Science Jurnal Ilmiah Computer Science The Indonesian Journal of Computer Science Control Systems and Optimization Letters ASEAN Journal for Science and Engineering in Materials ASEAN Journal of Educational Research and Technology
Zangana, Hewa Majeed
Unknown Affiliation
Aerospace Engineering Automotive Engineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

Published : 35 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 35 Documents
Search

 1   2   3   4 
Exploring Image Representation and Color Spaces in Computer Vision: A Comprehensive Review Zangana, Hewa Majeed; Mohammed , Ayaz Khalid; Sallow , Zina Bibo; Mustafa , Firas Mahmood
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3998

Abstract

This paper presents a comprehensive review of image representation and color spaces in the domain ofcomputer vision. Image representation serves as the foundation of computer vision systems, encompassingtechniques such as pixel-based, vector-based, and feature-based representations. Color spaces provide astandardized framework for encoding color information in digital images, with popular models includingRGB, HSV, Lab, and CMYK. The paper explores fundamental concepts, comparative analysis, practicalapplications, and future directions in image representation and color spaces. Insights gained from the reviewhighlight the significance of these concepts in various computer vision applications, including objectrecognition, image segmentation, and image enhancement. Future research directions include addressingchallenges such as achieving color constancy and developing adaptive color space selection techniques. Byleveraging the findings from this review, researchers and practitioners can advance the state-of-the-art incomputer vision and develop more robust and effective systems for real-world applications.
Evolution of Artificial Intelligence (AI)-driven Information Systems in Higher Education: A Review Karin, Juliana; Dharmayanti, Dian; Luckyardi, Senny; Soegoto, Eddy Soeryanto; Ximmataliyev, Dostnazar; Yusof, Mohd. Kamir; Chochole, Tomáš; Zangana, Hewa Majeed
ASEAN Journal of Educational Research and Technology Vol 5, No 3 (2026): AJERT: VOLUME 5, ISSUE 3, December 2026
Publisher : Bumi Publikasi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Artificial Intelligence (AI) has fundamentally reshaped the architecture of Information Systems (IS) within higher education institutions. This systematic literature review examines the technological transition from traditional management databases to intelligent, autonomous frameworks. By analyzing peer-reviewed studies published over the last decade, this paper identifies three major evolutionary phases: the automation of administrative tasks, the rise of adaptive learning platforms, and the integration of predictive analytics for student success. The findings highlight how AI-driven systems enhance operational efficiency and personalize student experiences while simultaneously introducing complex challenges regarding data ethics and algorithmic bias. This review provides a comprehensive synthesis of current trends, offering a strategic roadmap for educators and technologists to navigate the future of intelligent academic ecosystems.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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.
K-Nearest Neighbors for Smart Solution Transportation: Prediction Distance Travel and Optimization of Fuel Usage and Charging Recommendations for ICE Vehicles Based in Surabaya Baskoro, Farid; Aribowo, Widi; Shehadeh, Hisham; Zangana, Hewa Majeed; Putro, Wahyu Sasongko; Dwiyanti, Sri; Nurdiansyah, Aristyawan Putra
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.15068

Abstract

Surabaya ranks 9th in Southeast Asia and 44th globally in the TomTom Traffic Index, with an average travel time of ±22 minutes for a 10 km distance, longer than Jakarta’s ±20 minutes. Given these traffic conditions, this study examines the application of the K-Nearest Neighbors (KNN) algorithm to predict vehicle travel distance based on remaining fuel consumption and provides recommendations for the nearest Gas Station (SPBU) based on the predicted distance. The study seeks to provide accurate distance predictions and recommend the nearest Gas Station (SPBU) for users based on fuel consumption and the predicted route, helping to navigate Surabaya’s congested traffic efficiently. The data used includes various levels of fuel consumption: 0.02, 0.06, 0.10, 0.14, 0.16, 0.20, and 0.24 liters for engines of 110, 125, and 150 cc. The model evaluation results, using three metrics: MAE, MAPE, and RMSE show that KNN performs excellently at low fuel consumption levels. At a consumption rate of 0.02 liters, the model produces a low MAE of 0.347, MAPE of 31.21%, and RMSE of 0.40, indicating minimal prediction error. The model's performance remains consistent at a consumption of 0.06 liters with MAE of 0.330, MAPE of 9.90%, and RMSE of 0.41, demonstrating a high level of accuracy. Technically, the implementation of this model can help reduce traffic congestion by directing vehicles to the nearest gas stations, thereby minimizing sudden stops on the road, improving traffic flow, and reduce wasted time spent searching for distant gas stations.
Co-Authors Abdulazeez, Adnan M Abdullah , Dilovan Taha Abdullah, Dilovan Taha Abualigah, Laith Al-Karaki, Jamal N. Ali , Natheer Yaseen Ali, Natheer Yaseen Amaliah, Fithrotul Irda Anastasia Lidya Maukar Anik Vega Vitianingsih As’ad Shidqy Aziz Ayaz khalid Mohammed B, Nur Vidia Laksmi Bazeed, Sameer Mohammed Salih Beitollahi, Hakem Bobi Kurniawan, Bobi Cao, Xinwei Chochole, Tomas Dharmayanti, Dian DWI CAHYONO Eddy Soeryanto Soegoto Farid Baskoro Firmansyah, Deden Hassan, Noor Salah Husain, Mamo Muhamad Karin, Juliana Li, Shuai Lidya Maukar, Anastasia Luckyardi, Senny Ma'rifani Fitri Arisa Mahmood Mustafa, Firas Maulana, Hanhan Mirza, Mohammed Aquil Mohammed , Ayaz Khalid Mohammed, Aquil Mirza Mohammed, Ayaz Khalid Mohammed, Harman Salih Muhamad, Sabat Salih Mustafa , Firas Mahmood Mustafa, Firas Mahmood Natheer Yaseen Ali Nurdiansyah, Aristyawan Putra Obeyd, Salah Ramadan Oliva, Diego Omar , Marwan Omar, Marwan Omar, Naaman Putro, Wahyu Sasongko Rafdhi, Agis Abhi Rizal, Moch Arif Samsul Salih, Azar Abid Sallow , Zina Bibo Sallow, Amira Bibo Sallow, Zina Bibo Salsabilah, Azka Septiani, Riska Endah Shehadeh, Hisham Slamet Riyadi, Slamet Riyadi Sri Dwiyanti Sulaiman, Maryam A. Wani, Sharyar Wen, Goh Kang Widi Aribowo Ximmataliyev, Dostnazar Yusof, Mohd. Kamir Zeebaree, Subhi R. M.