In the last few decades, Information and Communication Technology (ICT) has featured prominently ... more In the last few decades, Information and Communication Technology (ICT) has featured prominently in transforming business practices. It has redefined our social existence. A huge number of IT devices such as computers, monitors, printers, scanners, copiers and fax machines, digital duplicators, multi-function devices, and mailing machines are increasingly produced everyday to support and fulfill operational needs of the organization. These IT devices contribute to global warming by producing CO2 emissions and contributing to the greenhouse effect. This is due to the fact that all phases on the IT product lifecycle produces an environmental impact. This research develops a green IT framework to implement and sustain green IT implementation and to apply this framework to UTM faculties/unit to assess the current capability maturity level of green IT practices for IT product lifecycle. The framework covers the green IT best practices in three phases of IT product lifecycle, namely procu...
A CBT Framework for Secondary Schools of Saudi Arabia
In this era of advanced technology, the learning paradigm is shifting from traditional teacher to... more In this era of advanced technology, the learning paradigm is shifting from traditional teacher to student model of pedantry to e-learning. There are numerous e-learning environments that use modern technologies in which assessment plays an important role to measure student progress. In this milieu, traditional paper based testing is unsuitable, hence, e-Assessment (Computer Based Testing or CBT) was introduced to overcome archaic limitations and streamline evaluation procedures. E-Learning is growing and has become popular, even common place, in a few sectors of Saudi Arabia's Secondary Schools, for which the Ministry of Higher Education continually strives to improve. But due to a lack of suitable planning and evaluation protocols, limited reviews of these efforts have been recorded. This paper, therefore, proposes a framework that may help improve CBT implementation in Saudi Arabia, specifically at the secondary level. A survey of six schools in Saudi Arabia was made to valida...
A Review of Factors Affecting the Sharing of Knowledge in Social Media
The success of knowledge management depends on how the knowledge is shared. Media such as Social ... more The success of knowledge management depends on how the knowledge is shared. Media such as Social Network, Blogs, Wikis and Podcast Forums have emerged as innovative online tools that affect knowledge sharing. As a result, many researchers have endeavored to define factors that affect knowledge sharing (KS) in social media. However, none of these efforts have either identified or categorized these factors in a comprehensive manner. Rather, different researchers focused on specific factors within different contextual milieus. Hence, this paper presents as systematic literature review in an attempt to identify all factors that affect the sharing of knowledge in social media and to provide a systematic categorization. We identified 120 papers from recognized online databases such as ISI, Sciencedirect, IEEE Explore, ABSCOhost, Compendex, and the CAM digital library that provided data on KS in social media and selected 15 of these for a detailed study. The major outcome of this study was...
Crime prediction becomes very important trend and a key technique in crime analysis to identify t... more Crime prediction becomes very important trend and a key technique in crime analysis to identify the optimal patrol strategy for police department. Many researchers have found number of techniques and solutions to analyze crime, using data mining techniques. These studies can help to speed up and computerize the process of crime analysis processes. However, the pattern of crime is flexible, it always changes and grows. With social media, user posts and discusses event publicly. These textual data of every user has contextual information of user’s daily activities. These posts generate unstructured data that can be used for data prediction. As shown by previous research, twitter sentiment enable to predict crime in Chicago, United States. However, existed model on crime prediction was incorporating the use of socio factors. Therefore, the study aims to model crime prediction using social media content with additional socio-factors. The research approach is consisted of a combination ...
Many researchers have addressed the impact of ICT as the cause of global warming, climate change,... more Many researchers have addressed the impact of ICT as the cause of global warming, climate change, and sustainability. This has encouraged further research in the area of Green IT as well as many sustainable frameworks of Capability Maturity such as SICT, IT CMF and the ITIL Maturity Model. In line with this drive, there is a need to search for a sustainable framework of Capability Maturity for the lifecycle of IT products. This paper proposes a sustainable framework of Capability Maturity for IT product lifecycles by providing IT users (consumer or organization) with a concrete guideline for practicing Green IT in the various levels of capability maturity. The product lifecycle includes Procurement, Usage, and Reuse/Disposal phases. IT and lab managers in the Faculty of Computing, UTM, will be involved in the framework verification. The framework verification will be conducted by using the card-sorting technique and interviews.
Many researchers have addressed the impact of ICT as the cause of global warming, climate change,... more Many researchers have addressed the impact of ICT as the cause of global warming, climate change, and sustainability. This has encouraged further research in the area of Green IT as well as many sustainable frameworks of Capability Maturity such as SICT, IT CMF and the ITIL Maturity Model. In line with this drive, there is a need to search for a sustainable framework of Capability Maturity for the lifecycle of IT products. This paper proposes a sustainable framework of Capability Maturity for IT product lifecycles by providing IT users (consumer or organization) with a concrete guideline for practicing Green IT in the various levels of capability maturity. The product lifecycle includes Procurement, Usage, and Reuse/Disposal phases. IT and lab managers in the Faculty of Computing, UTM, will be involved in the framework verification. The framework verification will be conducted by using the card-sorting technique and interviews.
Being one of the most widely used social media tools, Twitter is seen as an important source of i... more Being one of the most widely used social media tools, Twitter is seen as an important source of information for acquiring people's attitudes, emotions, views and feedbacks. Within this context, Twitter sentiment analysis techniques were developed to decide whether textual tweets express a positive or negative opinion. In contrast to lower classification performance of traditional algorithms, deep learning models, including Convolution Neural Network (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM), have achieved a significant result in sentiment analysis. Although CNN can extract high-level local features efficiently by using convolutional layer and max-pooling layer, it cannot effectively learn sequence of correlations. On the other hand, Bi-LSTM uses two LSTM directions to improve the contexts available to deep learning algorithms, but Bi-LSTM cannot extract local features in a parallel way. Therefore, applying a single CNN or single Bi-LSTM for sentiment analysis cannot achieve the optimal classification result. An integrating structure of CNN and Bi-LSTM model is proposed in this study. ConvBiLSTM is implemented; a word embedding model which converts tweets into numerical values, CNN layer receives feature embedding as input and produces smaller dimension of features, and the Bi-LSTM model takes the input from the CNN layer and produces classification result. Word2Vec and GloVe were distinctly applied to observe the impact of the word embedding result on the proposed model. ConvBiLSTM was applied with retrieved Tweets and SST-2 datasets. ConvBiLSTM model with Word2Vec on retrieved Tweets dataset outperformed the other models with 91.13% accuracy.
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Papers by Sakirin Tam