Muhamad Hariz Bin Muhamad Adnan

Muhamad Hariz Bin Muhamad Adnan
Universiti Pendidikan Sultan Idris (UPSI) | upsi · Department of Computing

Ph.D. in Information Technology

About

24
Publications
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114
Citations
Introduction
Dr. Muhamad Hariz bin Muhamad Adnan is a lecturer, trainer, and researcher of Artificial Intelligence, Data Science, Information Technology, Computer Science, and Web Development. My main interest lies in the autonomous decision making using algorithms to help humans make decisions such as in negotiations. Particular interest is in the development of a Machine Learning algorithm that analyzes data to make informed decisions.

Publications

Publications (24)
Book
Full-text available
This book provides in depth knowledge about critical factors involved in the success of pervasive healthcare. The book first presents critical components and importance of pervasive healthcare. The authors then give insight into the pervasive healthcare information systems and key consideration related to remote patient monitoring and safety. The b...
Article
Double auction is becoming the preferred negotiation protocol for cloud service negotiation due to its economic efficiency, capability in facilitating dynamic pricing, and suitability for handling a large number of customers and service providers. However, as far as this research work is concerned, there is no framework using double auction that si...
Article
Full-text available
Recently, the promotion of Science, technology, engineering and mathematics (STEM) education has become the highlight due to the shortage in the STEM workforce. Surprisingly, the enrolment rates in STEM degrees are still low in many countries. Social media has been identified as one of the main platforms that can help to increase prospective studen...
Article
Full-text available
Recent works using hyper-heuristics for solving clustering problems have been focusing on Genetic Algorithm. However, to the best of this research knowledge, no work is using hyper-heuristics dedicated for tuning the Genetic algorithm`s chromosome size for automatic clustering problem. The ability to tune the chromosome size is important because it...
Article
Full-text available
Many double auction frameworks have been proposed for cloud service negotiations [1]. However, the frameworks are not able to accommodate both the heterogeneous cloud services and multi-attributes negotiation simultaneously. Therefore, this paper proposed a double-auction framework to accommodate heterogeneous cloud services and multi-attributes ne...
Article
Full-text available
The global concern about a new pandemic associated with the insufficiency of vaccines has necessitated basic practices of handwashing to get prevention in Covid-19 disease in modern health issues. At this point, due to that, the researchers develop a simple mobile application engaging augmented reality to educate the urban and rural community on a...
Article
This article aims to contribute in securing information technology (IT) systems and processes for information security by utilizing malware risk detection for decision-making processes to mitigate cyber-attacks. It has potential to be a real threat to the businesses and industrial applications. The risk management is an essential component where it...
Article
The global concern about a new pandemic associated with the insufficiency of vaccines has necessitated basic practices of handwashing to get prevention in Covid-19 disease in modern health issues. At this point, due to that, the researchers develop a simple mobile application engaging augmented reality to educate the urban and rural community on a...
Chapter
Full-text available
Double auction-based mechanisms have gained considerable attention as autonomous cloud service negotiation because it has been proven to be economically efficient and possesses the ability to accommodate multiple buyers and sellers. The main objective of this paper was to outline the limitations of the practically tested double auction mechanisms i...
Article
Full-text available
A cloud service customer that has special QoS requirements may start negotiation process with the service providers. In negotiation, strategies are important to satisfy own needs, beating the competition and ensure successful negotiation. Business Level Objectives (BLOs) are important strategy metrics to achieve organization`s business goals in neg...
Article
Childhood obesity is a very worrying global epidemic and the Malaysian children have shown alarming statistics. Therefore, obesity and overweight predictions at an early age are important. This paper presents performances of eleven data mining techniques, that are sensitivity, specificity and accuracy tested using 320 Malaysian children datasets th...
Article
Full-text available
Big players in cloud service market like Microsoft, Amazon and Google keeps changing their service price. Increasing cloud service offerings have motivated cloud providers to develop cloud service marketplace such as AWS, Google Apps and Cloud Surfing. However, these marketplaces lack dynamic pricing mechanism. The idea of dynamic pricing in the cl...
Conference Paper
Full-text available
Autonomous negotiation needs certain protocol, a set of rules that defines the interaction boundaries between negotiating agents. This paper aims to allow readers, particularly agent-based autonomous negotiation designers to understand and differentiate various agent-based negotiation protocols. This paper reviews one-to-one, concurrent one-to-many...
Article
Full-text available
Even by using the data mining, many weaknesses still existed in childhood obesity prediction and it is still far from achieving perfect prediction. This paper studies previous steps involved in childhood obesity prediction using different data mining techniques and proposed hybrid approaches to improve the accuracy of the prediction. The steps take...
Conference Paper
Childhood obesity is an increasing health problem that is being faced globally and also in Malaysia. Obesity may lead to many diseases such as heart attack and diabetes. Obese children are prone to stay obese after growing up. So, it is important to reduce obesity right from childhood. Persuasive technology can be used to motivate people to change...
Conference Paper
Full-text available
Naïve Bayes is a data mining technique that has been used by many researchers for predictions in various domains. This paper presents a framework of a hybrid approach using Naïve Bayes for prediction and Genetic Algorithm for parameter optimization. This framework is a solution applied to the childhood obesity prediction problem that has a small ra...
Article
Data mining techniques have been used in past researches to predict childhood obesity, but the results are still inadequate. The purposes of this paper are to use significant parameters for childhood obesity prediction, to study suitable data mining techniques for childhood obesity predictions, and to propose a hybrid data mining technique. The pro...
Conference Paper
Obesity is a common issue nowadays. The numbers of obese people are increasing every year. There are evidences that childhood obesity persists into adulthood. Predicting obesity at an early age is both useful and important because preventive measures and proper interventions can be applied if the children indicated a high risk of obesity. However,...
Article
In this paper we present data mining and its utilization for childhood obesity prediction. Data mining was widely used in many childhood obesity prediction systems. Predicting obesity at an early age is both useful and important because the number of obese patients is increasing while its main cause cannot yet be defined. The ability to predict chi...

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