Pendidikan merupakan komponen terpenting dalam membentuk kecemerlangan sesebuah negara. Selaras dengan Pelan Pembangunan Pendidikan Malaysia (PPPM-PT) 2015-2025 yang inginkan transformasi dalam pendidikan, ICT memainkan peranannya tersendiri. Adaptasi budaya ‘Bring Your Own Device’ (BYOD), Virtual Desktop Infrastructure (VDI), ‘flip classroom’ dan ‘student centered learning’ menjadi kayuukur kepada sesebuah Universiti sejauh mana perkembangan dan keupayaan Universiti dalam memenuhi keperluan semasa pelajar. Peruntukan bajet yang semakin meruncing menjadi persoalan pokok dalam memastikan operasi dan perkhidmatan ICT dapat terus diberikan kepada pelajar dengan keperluan teknikal yang semakin mencabar. Makmal komputer merupakan aset terbesar bagi menyokong teras Pengajaran dan Pembelajaran (P&P) di sesebuah Universiti. Perkakasan komputer yang usang, kos penyelenggaraan yang tinggi dan perolehan perisian yang khusus bagi setiap Fakulti memerlukan pengurusan makmal yang lebih sistematik dan kos efektif . Mulai tahun 2014, pihak GOAL-ITQAN telah memulakan perjalanan alternatifnya dalam menguruskan makmal komputer yang lebih kos efektif melalui teknologi Clouddesk. Teknologi ini menjanjikanTotal Cost of Ownership (TCO) yang rendah dengan memanjangkan jangka hayat sesebuah komputer dan pelaksanaan spesifikasi teknikal yang minima.

This study is to construct the Graduates Employability Model using classification task in data mining. To achieve it, we use data sourced from the Tracer Study, a web-based survey system from the Ministry of Higher Education, Malaysia (MOHE) for the year 2009. The classification experiment is performed using various Bayes algorithms to determine whether a graduate has been employed, remains unemployed or in an undetermined situation. The performance of Bayes algorithms are also compared against a number of tree-based algorithms. Information Gain is also used to rank the attributes and the results showed that top three attributes that have direct impact on employability are the job sector, job status and reason for not working. Results showed that J48, a variant of decision-tree algorithm performed with highest accuracy, which is 92.3% as compared to the average of 91.3% from other Bayes algorithms. This leads to the conclusion that a tree-based classifier is more suitable for the tracer data due to the information gain strategy.

There are many potential and good open source software (OSS) products available in the market with free license. However, with various choices, the adoption rate is still low among OSS potential users because there is not an agreed acceptable set of criteria to evaluate and decide varieties of OSS products, with little documentation and user manuals, and immature products. Therefore, the users need to consider on how to improve decision making on selecting the most suitable OSS products. In this paper, the background research on the proposed OSS adoption and criteria of selection are discussed and explored which then moves to the implementation of the My Open Source Software Toolkit (MyOSST) v1.0. The analytical hierarchy process (AHP) was applied for selecting the most suitable OSS products and assisting the potential user for deciding the OSS products based on their preferred selection criteria. The toolkit will support the OSS adoption process with proposed criteria selection and pair wise comparison. The toolkit was tested and validated by IT professionals capable to assist the decision making on selecting an appropriate OSS product.

There are many potential and good open source software (OSS) products available on the market with a free license. However, with various choices, the adoption rate is still low among potential users because there is not an agreed acceptable set of criteria to evaluate and select various OSS. The criteria of selection may differ between the stakeholders within the organisations. There is a tendency that the user may have a biased perception of an OSS’s characteristics or capabilities for solving problems when selecting OSS products. Other restrictions are caused by inadequate documentation and user manuals, and immature products. Therefore, the users need to consider how to improve their decision making when selecting the most suitable OSS products. In this paper, the background research on the proposed OSS adoption and criteria of selection are discussed and explored. Then the research methodology, processes and implementation of the My Open Source Software Toolkit (MyOSST) v1.0 are covered. The analytical hierarchy process (AHP) was applied on the selection process and for the purpose of assisting the potential user to decide on the OSS products based on their preferred selection criteria. MyOSST v1.0 was tested and validated by IT professionals in one of the Malaysian universities. The results show that the tool is capable of assisting the decision making process for selecting an appropriate OSS product.