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Forming an optimal collaborative team is achieved using members characteristics to improve team efficiency. A team's performance may have a negative effect when a team is formed randomly. Moreover, it is quite impossible to achieve an optimal team manually as the formation can expand into countless possibilities. Hence, this paper presents a decisionmaking framework for collaborative team formation by incorporating Fuzzy Logic and Genetic Algorithm (Fuzzy-GA). The framework has been initiated by combining effective team formation factors such as skills, trust, leadership, and individual performance. Unified Theory of Acceptance and Use of Technology (UTAUT) is utilised to survey the readiness and technology acceptance of the organisations' employees in adopting the proposed decision-making approach to form a collaborative team. The UTAUT survey had proven that behavioural intention (BI) had a positive impact on the performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions (FC). However, behavioural intention (BI) had a negative impact on the voluntariness of use (VU); thus the transformation of collaborative team formation must be further explored to increase the team's voluntarism towards this automated collaborative team formation.

Many organisations have been struggling to defend their cyberspace without a specific direction or guidelines to follow and they have described and identified cyber attack as a devastating potential on business operation in a broader perspective. Since then, researchers in cyber security have come out with numerous reports on threats and attack on organisations. This study is conducted to develop and propose a Cyber Security Defence Policies (CSDP) by harmonising and synthesizing the existing practices identified from the literature review. Observation and questionnaire were adopted to evaluate, review and collect data under ethical agreement from 10 organisations. The validation is based on the principal components for the proposed CSDP and the proposed CSDP, using SPSS as the statistical tool. The result shows that, the validation of the proposed CSDP by 20 experts reveals a standard deviation of 0.607, 0.759, 0.801, 0.754, 0.513, 0.587 and 0.510 on each of the principal components without a missing value respectively. While the correlation matrix and the reproduced correlation matrix for the proposed CSDP indicated 61% and the percentage of acceptance on the principal components for the proposed CSDP are higher than 50%. Therefore, from the outcome, it has shown that the acceptance responds towards the proposed CSDP and the result from the principal components analysis (eigenvalue analysis) are significant enough for implementation and can be adopted by organisations as a guidelines for organisation cyber security practices.

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Objectives: The main aim of this study was to use text mining on social media to analyze information and gain insight into the health-related concerns of thalassemia patients, thalassemia carriers, and their caregivers.Methods: Posts from two Facebook groups whose members consisted of thalassemia patients, thalassemia carriers, and caregivers in Malaysia were extracted using the Data Miner tool. In this study, a new framework known as Malay-English social media text pre-processing was proposed for performing the steps of pre-processing the noisy mixed language (Malay-English language) of social media posts. Topic modeling was used to identify hidden topics within posts shared among members. Three different topic models—latent Dirichlet allocation (LDA) in GenSim, LDA in MALLET, and latent semantic analysis—were applied to the dataset with and without stemming using Python.Results: LDA in MALLET without stemming was found to be the best topic model for this dataset. Eight topics were identified within the posts shared by members. Of those eight topics, four were newly discovered by this study, and four others corresponded to the findings of previous studies that used an interview approach.Conclusions: Topic 2 (the challenges faced by thalassemia patients) was found to be the topic with the highest attention and engagement. Healthcare practitioners and other concerned parties should make an effort to build a stronger support system related to this issue for those affected by thalassemia.