Assessment of the Effectiveness of Risk Management Practices in the Performance of IT Projects

This study assessed the effectiveness of risk management practices in the performance of IT projects. This study was guided by Project Management Theory. The study employed a mixed research approach, a mixed research approach and descriptive research design. The study was conducted at the Tanzania Revenues Authority Head Office in Dar es Salaam, the targeted population of this study is 200 and the sample size was 133 obtained suing simple random sampling techniques and purposive sampling techniques. in this study data was analysed using quantitative and qualitative techniques. The findings show that management practices are very essential in the implementation of the IT projects. It was also shown that effective project implementation depends much on the effective risk management practice because it is through them that risk can be mitigated for the sustainability of the IT projects. moreover, the results obtained through correlation analysis shows that Risk Assessment Practices (RAP) correlated (r (125)> .568, P< .000), Risk Response Practices (RRP) correlated (r (125)> 452, P < .000), Risk Response Practice (RRP) and the performance of IT Projects (PIP). Lastly Monitoring and Control Process (MCP) had a correlation of (r (125)> 652, P < .000. The results of this study concluded that there is a positive and significance relationship between risk management practices and the performance of IT projects. Despite of these supportive findings this study recommended for the proactive management of project risk because IT project implementation is subject to the limitation challenges and risks, thus through proactive management of project risk a comprehensive assessment of risk and preparation of a suitable management plan can be activated. The study recommended further research be conducted on the assessment of the effectiveness of implementation approaches toward project sustainability

Belief rule-base expert system with multilayer tree structure for complex problems modeling

Belief rule-base (BRB) expert system is one of recognized and fast-growing approaches in the areas of complex problems modeling. However, the conventional BRB has to suffer from the combinatorial explosion problem since the number of rules in BRB expands exponentially with the number of attributes in complex problems, although many alternative techniques have been looked at with the purpose of downsizing BRB. Motivated by this challenge, in this paper, multilayer tree structure (MTS) is introduced for the first time to define hierarchical BRB, also known as MTS-BRB. MTS- BRB is able to overcome the combinatorial explosion problem of the conventional BRB. Thereafter, the additional modeling, inferencing, and learning procedures are proposed to create a self-organized MTS-BRB expert system. To demonstrate the development process and benefits of the MTS-BRB expert system, case studies including benchmark classification datasets and research and development (R&D) project risk assessment have been done. The comparative results showed that, in terms of modelling effectiveness and/or prediction accuracy, MTS-BRB expert system surpasses various existing, as well as traditional fuzzy system-related and machine learning-related methodologie