000			02108nam a22002417a 4500
003			FT8771
005			20251106132016.0
008			251106b ||||| |||| 00| 0 eng d
041			_aengtag
050			_aT58.64 L36 2025
082			_a.
100	1		_a Lao, Camila T.; Paraiso, Hanna Nicole S.; Mendoza, James Richard L.
245			_aAllocate it: Optimization of resource allocation of IT consultancies using a decision support system
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: In the IT industry, efficient resource allocation is crucial, yet many smaller consultancies still rely on outdated manual systems, leading to missed deadlines and overstretched teams. In response, Allocate IT, a web-based platform, was developed to streamline staff assignments based on skills and availability, improving efficiency. Utilizing a decision support system and frequency counting algorithm, it allows project managers to quickly match the right. The system underwent evaluation using software quality standards, achieving a user satisfaction score of 4.00 out of 5. High ratings were received in Functional Suitability with scores of 4.06 for Completeness and 4.2 for Correctness, in Reliability with Consistency at 4.1 and Availability at 4.2, and in Usability, with a notable 4.5 for User Interface Aesthetics. While performance across categories was strong, there is room for improvement in Stability, rated ay 3.96, and Appropriateness at 3.93. A confusion matrix analysis revealed that while the model excels in predicting correct resource allocations, it struggles with misallocated cases, indicating the need for refinement. Despite these challenges, Allocate IT represents a significant advancement in resource management IT consultancies, enhancing efficiency and effectiveness.
526			_aF
655			_aacademic writing
942			_2lcc _cMS
999			_c37042 _d37042