Browsing by Author "Roslina Othman, Ph.D"

This dissertation reports on the commentaries on cryptocurrencies from Muslim scholars and experts in social media based on an information dissemination model. In recent years, cryptocurrencies, especially Bitcoin, have become increasingly popular since it was launched in 2009. People were attracted to know and understand this type of technology due to its unique characteristics. The research objectives were to identify commentaries on cryptocurrencies offered by Muslim scholars and experts in social media, to identify the themes of the commentaries made by Muslim scholars and experts related to cryptocurrencies extracted from the social media, and to explore the responses of social media users to the commentaries made by the Muslim scholars related to cryptocurrencies. The methods used in this research were content analysis to identify and analyse the commentaries from nine selected Muslim scholars and experts for producing topics and themes, and an online survey questionnaire completed by 115 respondents. This research found the themes extracted from the identified commentaries made by Muslim scholars on social media as follows: 1. Cryptocurrency, 2. Bitcoin, and 3. Blockchain. Social media users responded to the statements derived from the commentaries and themes are as follows; first, 74% of 115 respondents agreed with cryptocurrency as a currency in digital form that is intangible and not issued by a government but issued by a single community, and; second, 70% of 115 respondents agreed with the fact that cryptocurrency was built from specific code numbers. These findings indicated that 1. (64% of 85) respondents that agreed with cryptocurrency are a currency in digital form that is intangible and not issued by a government but issued by a single community were informed on cryptocurrencies, and 2. (62% of 81) respondents that agree with cryptocurrency are built from specific code numbers were informed on cryptocurrencies. In conclusion, the commentaries on cryptocurrencies made by the Muslim scholars and experts explained the issues related to cryptocurrencies and were well-responded by social media users. This research contributed to the extraction of the topic commentaries and themes of commentaries, and the social media user responses to the commentaries. The further research works included Muslim scholars and experts in other countries and extended to examine how social media influences user perceptions towards cryptocurrencies.

The concept of improving oneself by gaining knowledge and insight regarding tasawwuf is gaining popularity nowadays. Even though various materials and books are available but only for reading, it is up to the user to decipher what necessary actions and knowledge is required to enhance oneself in the spiritual realm. However, a system offering the assessment of a person’s current state with the opportunity to learn the ways of spiritual enhancement in religious context is not there. For any kind of improvement to be beneficiary and stable, they need to transpire in incremental stages. The system will have a familiarity with states and transitions, which is the essence of finite state models. Finite state models are very versatile, applicable to the analysis and design of both abstract and physical systems. So, there is a need for a finite state model that will provide relevant search criteria for the user to not only assess his or her current state but also to provide access to resources and information that will help the user to journey through the states accordingly for self-improvement. First an extraction framework has been developed to manually extract and assess the relevancy of texts from the book Minhaj al ‘Abidin authored by Imam Ghazali (r.a) to identify the states and based on the physical and psychological constructs the triggers and that activates the transitions from one state to the other. Then a finite state model has been developed based on the relevant texts as states and triggers, along with the concept of attributes has been introduced as a tool to provide feedback to the users to improve. Design based research methodology was used for iterative analysis, design, development, and implementation of the finite state model and text extraction model. A prototype system entitled Self-Help Maqam-Based Search system based on the finite state model designed, was built, this allowed the experimental validation of the finite state model and text extraction framework. Results from performance testing using open-source tools and user feedback proved the efficacy of using finite state modelling in the system. And quantitative data collected from the system and after being statistically analyzed showed a positive correlation between hours spent, age group and attainment of higher maqam levels. This validates that self-help interventions using religion as content do help in the process of spiritual enhancement.

The holy Qur' an is the first fundamental resource of legislation and law in the Muslim community. The Qur'anic text has been covered by Islamic scholars to offer Qur'anic knowledge quickly and systematically, such as digital Qur'an, and Qur'anic computing. This is performed using the techniques of text mining to automate the Qur'anic text. The classification of Qur' anic verses is one of the focal points in many research, which is conducted through automatic Qur' anic classification. The purpose of Qur' anic classification is to assign the most appropriate topics that are predefined to a specified Qur'anic verse according to its content. However, some properties in the Qur'anic topics such as imbalanced classes could weaken the perfonnance of classification when these classes are classified using traditional classification. Imbalanced classes occur when the sample number of classes in the dataset is not equal. As noticed in the dictionary used in this research, many Qur'anic topics are unequal in the number of verses, which means the problem of imbalanced classes will occur when these topics are classified together using traditional classification. The main problem that this study tries to solve is obtaining equal accuracies for all classes of Qur'anic topics during the classification process. Therefore, this study attempts to explore a new approach to categorise the Qur' anic topics based on imbalanced learning and a genetic algorithm that is called optimisation learning. The technique of imbalanced classification was applied to solve the problem of imbalanced classes existing in the Qur' anic topics. The genetic algorithm was used as an optimisation objective before the implementation of classification. This optimisation was performed for the samples of Qur' anic text to adjust the convergence and spacing between the samples, whether in the same class or among the classes. This adjusting leads to improve the performance of Quranic topics classification. Three cases of optimisation were experimented in this study using the proposed techniques: partial optimisation with oversampling, full optimisation without oversampling, and full optimisation with oversampling. These cases were implemented by using three new oversampling methods, Genetic Oversampling (GOS) and Harmonised Oversampling method based on Genetic Algorithm (HOGA-I and HOGA- 2). In conclusion, the third case of optimisation achieved the best results. Meanwhile, all proposed methods outperformed significantly the other famous methods that have been used widely to classify imbalanced datasets, which are Synthetic Minority Oversampling Technique (SMOTE), Random Undersampling (RUS), and Random Oversampling (ROS). According to the experiment results, GOS method outperformed SMOTE and ROS methods, which were the second best methods among the other previous methods in Specificity metric by I 2% using the validation technique of I 0- fold cross-validation. Meanwhile, HOGA-I method outperfonned the closest method in Matthews Correlation Coefficient (MCC) metric by 7% using the validation technique of training-testing. HOGA-2 method, which was the best among all proposed oversampling methods, outperfonned all closest methods in Sensitivity/Recall, Balanced Accuracy, and Geometric Mean (G-Mean) metrics by I 0% using the validation technique of I 0-fold cross-validation.

Libraries in most of the academic university always strive to serve the customers research needs. This include by investing on library online databases. Library online databases subscribed by the library were regarded as a main source for researchers. Many researchers investigated on the effectiveness of the electronic resources in the library. However, little is known on the impact of library online databases among academic members in Malaysia. The objective of the research, mainly is to evaluate the library online databases' effectiveness and their impacts on academic members. The participants of the study are from the Faculty of Engineering and Science in University of Malaya (UM), International Islamic University Malaysia (IIUM) and Universiti Teknologi Mara (UiTM). The research used a quantitative descriptive research design using the survey as a principal approach for data collection. A set of questionnaires comprised of three parts are used in the research. The data was analyzed using SPSS. As for data analysis, Descriptive statistics (frequencies, means, percentage, standard deviations) and analytical techniques such as correlation, regression and cross-tabulation were used. In correlation analysis, academic members’ satisfaction relationship with each factor was examined separately to measure the direction and strength of each relationship. In the second technique, regression analysis was used to ascertain which of the strongest explanatory power factors has when those factors are combined in a regression model. The findings of this research provide useful information on the impact of library online databases among academic members. Findings from this research can be used by university administrators in planning, evaluating and executing the use of library online databases. The findings conclude that there is a positive relationship between satisfaction and information quality, system quality and service quality.

This doctoral dissertation aimed to achieve three main objectives; defining Halal Research Comprehensive Index based on bibliometric study, constructing collection of halal food related Quranic commandments, and conducting a bibliometric study of halal food themes from online databases. This research is essentially, a descriptive study that emphasized subject epistemological origin in which definitions of halal from the Islamic knowledge were explored and exploited in the document retrieval process. In the subject analysis, a combination of reviews and bibliometric analysis was applied to explore the meaning and to extract research data. The mapping review defined halal concept epistemologically, in which translations of Quran verses were chosen to trace the origin of halal research according to the Islamic primary source of revealed knowledge. Concept definitions from halal governing bodies were also compared to gain insights into the governance of halal verifications and endorsements at the International level. The systematic literature review focused on the original concept, ‘halalan toyyiban’ where research papers from Scopus were extracted and analysed systematically. State-of-the-Art review collected the latest research works in halal and analysed the latest research themes. Al-Qaradawi (2001), ‘The Lawful and Prohibited in Islam’ was the main source of reference in the thematic citation analysis that corresponded to Al-Qaradawi’s categorization of halal with research data from Scopus. Citation network analysis on findings from Al-Qaradawi revealed halal business and halal social as the top themes. Data collections are from EBSCohost (1,400 documents), Emerald (307 documents), IEEE Xplore (48 documents), ProQuest (1,155 documents), and ScienceDirect (125 document), Scopus (1,492 documents), and Web of Science (1,217 documents) totalling 5,744 documents. All data are extracted between December 2018 to June 2019. Co-word or co-occurrence of terms from all collected data are identified and clustered. The research output is the Halal Research Comprehensive Index that was collectively a list of high impact halal research publications from the research analysis. This research utilizes several instruments namely, VOSviewer, GEPHI, and Microsoft Excel in data analysis. The research findings were mainly reviews and bibliometric analysis. Mapping review of halal definitions revealed similar descriptions of halal concept, conceptually and operationally. Systematic literature review identified ‘halal business’ and ‘halal social’ as the top two halal research topic in Scopus. Halal supply chain research topics were the main findings in the state-of-the-art review. The thesis output is the Halal Research Comprehensive Index to high impact halal research topics. Five major themes were identified in the co-word analysis; halal industry, halal forensics, halal slaughter, animal and meat sciences, halal consumerism and marketing, and halal gelatine.

The research aimed to propose a Knowledge Management (KM) model for creating service-based value for public university libraries in Bangladesh. The other Research Objectives (ROs) were to explore the current models of KM implemented by the university libraries, examine the current KM practices in public university libraries in Bangladesh, examine the critical success factors, and identify the challenges related to KM prac¬tice. The present research used both quantitative and qualitative approaches (mixed method). A pilot study was conducted to establish reliability and to validate the questionnaire. For the final survey, 1,060 questionnaires were distributed among the undergraduate (UG) and postgraduate (PG) students of five public university libraries in Bangladesh using a simple random sampling technique. Out of 1,060 distributed questionnaires, 811 usable questionnaires were returned, giving a response of 76.5%. This research also interviewed 11 Librarians/Deputy librarians/Assistant librarians of the selected public university libraries who hold the highest position at their university libraries. A purposive sampling method was used to determine the interviewees for the qualitative approach. Out of 13, Librarians/Deputy Librarians/Assistant librarians, 11 were interviewed, giving a response rate of 84.6%. The quantitative analysis found that users' familiarity with KM is moderately low. They learn about KM through courses provided by their respective departments and independent study through research literature. Users also agreed that KM is an alternate name for information management, and it is a modern librarianship discipline. It was found that establishing a solid infrastructure for future development, continuous training programs, utilizing technology accurately, and organizational Information and Communication Technology (ICT) structure are the critical success factors for designing and implementing a KM in public university libraries. At the same time, lack of awareness, problems with organizational culture, improper technology deployment, and inadequate support from management are the challenges related to KM prac¬tice in public university libraries in Bangladesh. The qualitative findings found that no formal KM programs are in place in any of these selected universities. The research also established that libraries are doing some resemblance of KM practices in their everyday work. The research found that tactful strategy for KM implementation, recruiting skilled manpower, a training program for staff and users, ICT infrastructure, and skilled manpower are the critical success factors of KM implementation in the public university libraries in Bangladesh. According to the findings, lack of budget, lack of user awareness, lack of trained staff, and obsolete technologies are the challenges for KM implementation in the library. Finally, the research proposed a model for public university libraries in Bangladesh. The model showed that the successful implementation of KM can bring benefits to libraries depending on the quality of the library services, critical success factors, users’ familiarity with KM, KM relevance to librarianship, and the potential contribution of various departments. Based on the findings of this research, the recommendations are given to the librarians and the higher authority of the university. The research was limited to only five public university libraries in Bangladesh. Finally, the research presented managerial and practical implications with further research directions. This research would be an excellent addition to the application of KM in the library of Bangladesh.

This dissertation reports the new normal practices in School Resources Centre (SRC), during the COVID-19 in Secondary Schools in Wilayah Persekutuan Kuala Lumpur. The research has explored some of the circumstances and practices in the SRC new-normal era of the pandemic. The objectives of the research were to explore the current situation and practice in SRCs during the new-normal era, to identify the SRC exit plan to operate during the COVID-19 pandemic, and to identify some of the challenges faced by Library Media Teacher (LMT) during this period. The research questions were also formulated based on the objectives. Survey questionnaires and interviews were applied to gather the data used for the research. The population of the research comprised all the LMT in secondary schools around Wilayah Persekutuan Kuala Lumpur. The questionnaires were distributed to the 104 LMT through their school email, of which only 82 responded and three of them also agreed to be interviewed. The findings of the research have provided an overview of the real situations in the SRC and its readiness in adapting to the new normal practices during the COVID-19 crisis. The findings will also be of great benefit to institutions that are interested in developing policies and practices regarding the COVID-19 pandemic. The long-term benefits of the research will provide some sort of recommendations for the SRCs to seek improvements in aligning their roles in supporting quality education and information services during the COVID-19 crisis in their school community.

This research develops an open science model for research data management at the Malaysia National Institutes of Health (NIH), a leading health research organization in the country. It addresses the challenge of low researcher participation observed during the initial implementation of the NIH-Data Repository System (NIH-DaRS). Recognizing the importance of open science in promoting collaboration, transparency, and accessibility of research, this research aimed at investigating the readiness of the researchers and institute to embrace open science practices. Several factors, spanning technical, motivational, economic, political, legal, and ethical realms, have been recognized as impediments to data sharing in advancing open science participation. However, these factors have been identified based on diverse institutions and organizations, prompting a need to recognize factors applicable to the Malaysian NIH context. To address this gap, an exploratory sequential mixed-method approach was employed. This approach consisted of qualitative data collection through semi-structured interviews with NIH management staff and quantitative data collected through an online survey from researchers working with the institute. Lastly, the developed model was presented to the NIH management for validation. The qualitative phase identified all possible factors influencing participation in open science through research data sharing and reuse, alongside the benefits and challenges of integrating the FAIR principles (Findable, Accessible, Interoperable, and Reusable) into research data management. On the other hand, the quantitative phase was used to test and confirm the research hypotheses derived from the qualitative findings using SEM (Structural Equation Modelling). Both findings were then triangulated to enhance the research's validity and credibility and provide a more comprehensive understanding of the phenomenon under study. The main contributions of this research are: (1) Providing an empirical understanding of the current practices and perceptions of open science among NIH researchers. (2) Proposing a comprehensive and evidence-based open science model for research data management that incorporates the FAIR principles, rewards and incentives, awareness and capacity building, policies and regulations, available platforms and repositories, trust and confidence, efforts and sacrifices, and data characteristics. (3) Recommending a set of guidelines and best practices for implementing open science at the NIH. (4) By meticulously developing a detailed and precise interview guide and questionnaire, this research not only advances practical, theoretical, and methodological knowledge on open science in the context of health research data management, but also sets a strong foundation for future research in this domain. The research concludes with implications for stakeholders, limitations, and directions for future research.

Sepsis is a severe threat to global health. Approximately, the mortality rate of sepsis in the Intensive Care Unit (ICU) is 42%. In 2017, 11 million sepsis-related deaths were reported among 49 million cases, 20% of all-cause of deaths worldwide. Detection and prediction of sepsis in earlier stage allow patients to get earlier care and better results, but sepsis is often unknown until the late stages. Substantial bodies of research studies on sepsis prediction have mainly focused on rules-based severity scores, which are transparent and straightforward; unfortunately, they have imperfect sensitivity and specificity in identifying and predicting sepsis. Typically, various sepsis predictions approach that would allow for predicting in an earlier stage, which can reduce the mortality rate and treatment cost. So, machine learning algorithms can be a choice for predicting sepsis. Therefore, this current thesis identified the features influencing early sepsis prediction and examining the features impelling the clinical severity scores used for the prediction of sepsis. The thesis also developed a hybrid optimal brain surgeon algorithm for sepsis prediction and tested the proposed algorithm's accuracy. The research methodology adopted for this thesis is an experimental simulation. The datasets used in this research were adopted from MIMIC-III, which comes with vast electronic health records. A systematic literature review was performed, and significant features of the MIMIC-III dataset for sepsis prediction were obtained by applying Automatic Backward Elimination (ABE) algorithm, Generalized Linear Model (GLM), and Correlation Matrix (CM). After that, the research built a hybrid-sepsis prediction model using machine learning techniques to train and test with selected features for model selection. Then Optimal Brain Surgeon (OBS) algorithm was used to simplify the architecture of the neural network for making an explainable deep learning-based sepsis prediction model. This is where hybridization has taken effect. The pruning algorithm OBS uses Hessian information and considers the time delay for measuring the saliency. Second-derivative information is used to compromise between the difficulty of the network and the training set error. The thesis's finding revealed that the AUROC of the predictive model was 0.882. The hybrid OBS algorithm pruned network is 80.0% with the same accuracy of the prediction model. This result indicates that the proposed hybrid model is efficient with high prediction accuracy and slight complexity compared with some previous prediction techniques. Early prediction of sepsis can reduce mortality rates and save treatment costs among ICU patients.

This research explored the readiness towards implementing Open Science (OS) initiatives in Malaysian comprehensive public universities; OS stands for a transition to a new, open. A collaborative way of conducting, publishing, and evaluating research is a system in which scientists and researchers worldwide can come together and contribute to all research processes. It also allows for sharing many valuable scientific discoveries beneficial to different aspects of human life at the end of the methods. This practice and procedure are implemented through the readiness and willingness of the stakeholders in most places. However, findings still show that most of the stakeholders were even not fully participating in the system. To achieve the objectives of this research, four comprehensive universities among the public universities in Malaysia were chosen to examine the readiness of the academic researchers and the professional librarians in these universities towards Open Science initiatives. Mixed-method research was implemented, where a questionnaire and interview were used to gather information from the respondents. A total of 255 responses was received from both the academic researchers and the library professionals for the quantitative method. A total of 6 librarians were also interviewed for the qualitative approach to complement the first method. At the end of the research, a triangulation was done to aggregates the significant findings of the research. The results indicated that the comprehensive public universities in Malaysia were partially involved in OS, even though the term was still new to most participants and where most of them assumed that OS is another term for open access. The institutional repository was the commonly known way these universities have been involved in the OS practice. However, only 10% to 30% of their contents were also available to the general public, while some Institutions only provide abstract to the public. The Institutions also provide the specializations, metadata, and the personal contact details of their researchers on their website, for those who may want to work with them. However, these institutions are still working on providing a policy on operating and fully engaging another aspect of the OS practices. While some recommended factors identified by the stakeholders to fully implement the OS practices were the need for more enlightenment on the system, more modern digital facilities or infrastructure such as high-speed internet, and well-managed and secured servers.

People share their opinion and information through social networks platforms such as Twitter, You Tube, and Facebook. Their shared opinions towards certain issues are sentiments that could be productive, constructive, or possibly controversial. These opinions are positive or negative sentiments. Sentiment analysis are done mainly on marketing and political issues. They focused on trends to improve their services to achieve their targeted audiences and customers. However, there is yet a need to conduct sentiment analysis on cultural psychology issues. Thus, this research aimed to analyse and categorize the sentiments people shared on a social network pertaining to the selected issues on topics in cultural psychology. The Zheng and Fang model was adapted for sentiment analysis. Three social networks were selected; You Tube, Facebook, and Twitter that offer search capability enabling the retrieval of posted comments and opinions. A sample of 100 cases based on the selected topics have been collected and formulated as queries. The queries retrieved the sentiments. The identified sentiments were analysed and classified as positive and negative and topically categorized based on a value system using WordStat8 and LightSIDE toolkit. The Prabowo and Thelwall combined model of sentiment analysis was referred to for categorization. The outcomes included a pool of positive and negative sentiments; and topic categorization developed based on sentiment analysis. Kappa, recall, precision and F-Scores were reported to range from -0.01 to 0.23, 0.06 to 1.00, 0.14 to 0.96, and 0.04 to 0.86 correspondingly. Overall, Kappa, precision, and F-scores ranged from very low to high ratios, except for the perfect recall.

This dissertation presented on Social Media Use in Malaysia and Indonesia: A Future Study. This research was expected to enhance the future of Muslim preparation especially Malaysia and Indonesia for the raise of proliferation related to social network uses, to improve social media usage. As in the Quran and Sunnah suggested, positive recommendation for the benefit of mankind, particularly the need to use it. The objectives were to explore the potentials related to social media use, to explore the emerging trends related to social media use, and to explore the future of social media use in Malaysia and Indonesia. The methods applied in this research were content analysis and Delphi methods. Triangulation from content analysis and Delphi method were also stated in this research. The result found out that websites on technology for future social media use forecasted the scenarios for near future social media use such as augmented reality, virtual reality, and user generated content needing plans on content for use. While the scenarios for far future social media use, which were personalized search bots, machine learning and fake news truth, needed plan for social media design and use. The experts viewed that the future social media use in Malaysia and Indonesia would involve sophisticated social media technology. The experts were concerned that the near future social media use in Malaysia and Indonesia would be reachable, uncontrollable, and unpredictable, where it would dominate people’s communication and daily activities. The experts were concerned that artificial intelligence would be in the mainstream to influence future social media use in Malaysia and Indonesia.

Nowadays, the need to employ a new technology to update, support education and enhance studying in general but specifically the Holy Quran is of great necessity. One of these new technologies that is often used is mind maps (mind mapping) as it has been used for decades in schools and colleges for note taking and learning. Even though mind maps are beneficial in terms of learning, creating maps after reading and understanding a text takes a long time. Mind maps were used in Holy Quran learning, but the majority of the learners use the traditional method of Quran memorization, which is based on repetition. The use of repetition in the process of memorization makes it difficult to memorize. Individuals require more time and they tend to forget what they have just memorized. In order to avoid these problems mentioned earlier, some researchers worked on creating mind maps of the Holy Quran and discussed the positive impact on using a manual drawn mind map in studying and memorizing the Holy Quran. Creating mind maps of one chapter of the Holy Quran took a long time. Researchers worked on automatic creation of mind maps for the English, Croatian and Indonesian languages but not for Arabic language. Based on the literature review of this research, there is no research emphasizing the creation of an automatic mind map of the Holy Quran. Therefore, the aim of this research is to develop an algorithm that automatically generates the topics based on the mind map of a set of verses in the Holy Quran. The general idea of the algorithm uses the frequency of the Arabic root word to find the topic of the verses. This work is significant because it will enhance the understanding and memorization of the Holy Quran by viewing the concepts in a way that is easy for the brain to perceive. Moreover, it could help extract new knowledge from the Holy Quran from the generated mind maps and facilitate the understanding of Tafsir. This research found the topics of all sets of verses based on the Topical Mushaf and Al-Duwayish mind map of Surat Al-Baqarah. The algorithm results were evaluated with topics of expert scholars and the error rate of the algorithm was 25% with the Topical Mushaf and about 35% with Al-Duwayish mind map topics. This work is limited to extract the topics from the Qur'anic verses as an input for the mind map drawing. This research contributes to the field of automatic generation of mind maps of the Holy Quran and provides the algorithm that automatically returns the topics of a set of Qur'anic verses.