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Andino Maseleno
Researcher at Universiti Tenaga Nasional
Publications - 195
Citations - 2553
Andino Maseleno is an academic researcher from Universiti Tenaga Nasional. The author has contributed to research in topics: Decision support system & Computer science. The author has an hindex of 21, co-authored 177 publications receiving 1900 citations. Previous affiliations of Andino Maseleno include Sultan Idris University of Education & Universiti Teknologi Malaysia.
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Hybrid optimization with cryptography encryption for medical image security in Internet of Things
TL;DR: This paper investigated the security of medical images in IoT by utilizing an innovative cryptographic model with optimization strategies, and identified a diverse encryption algorithm with its optimization methods with the most extreme peak signal-to-noise ratio values.
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Optimal feature-based multi-kernel SVM approach for thyroid disease classification
TL;DR: The novelty and objective of this proposed model as feature selection, it’s used to enhance the performance of classifying process with the help of improved gray wolf optimization.
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Big data emerging technology: Insights into innovative environment for online learning resources
Miftachul Huda,Andino Maseleno,Pardimin Atmotiyoso,Maragustam Siregar,Roslee Ahmad,Kamarul Azmi Jasmi,Nasrul Hisyam Nor Muhamad +6 more
TL;DR: A model reference is proposed which can be implemented with the technology in teaching and learning to improve student learning environment and outcomes and to enhance students’ development, performance and achievement in learning process in higher education.
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Hau-Kashyap approach for student’s level of expertise
Andino Maseleno,Miftachul Huda,Kamarul Azmi Jasmi,Bushrah Basiron,Ismail Mustari,Abdul Ghaffar Don,Roslee Ahmad +6 more
TL;DR: The results found that the stage level of belief that ranges combined from the level of expertise 1–12 was indicated that Hau-Kashyap approach can be determined to measure the learners’ expertise more fairly and easily.
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Exploring Adaptive Teaching Competencies in Big Data Era
Miftachul Huda,Andino Maseleno,Masitah Shahrill,Kamarul Azmi Jasmi,Ismail Mustari,Bushrah Basiron +5 more
TL;DR: The framework model is explored as a way for teachers in adapting big data to help their teaching performance especially in accessing the resources to support assessing the multi-channels of sources of knowledge to extract new insights of value in exploring the adaptive teaching competencies.