A Recommendation System of Training Plan to Accelerate Workforce Competency for Oil & Gas Company in Bintulu

NURSYAHIRA, SUHIB (2020) A Recommendation System of Training Plan to Accelerate Workforce Competency for Oil & Gas Company in Bintulu. [Final Year Project Report] (Unpublished)

[img] PDF
Nursyahira Binti Suhib - 24 pgs.pdf

Download (2MB)
[img] PDF (Please get the password from TECHNICAL & DIGITIZATION MANAGEMENT UNIT, ext: 082-583913/ 082-583914)
Nursyahira Binti Suhib.pdf
Restricted to Registered users only

Download (6MB)


To upskill each of the staff based on their respective specialties, superiors in Petronas MLNG decides what most suitable trainings are for the subordinate staffs. However, this process is time consuming as superior must decide the training based on each of the staff’s competency gap. To date, there has not been a solution that would ease the superior’s task in making decision faster. In this project, a collaborative-based recommendation system is developed in a web-based system to produce a list of training based for the staff. The main feature of this prototype is to recommend training for each of the staffs. The functional testing has been done to identify any error during system testing while a non-functional testing which was the survey method was done to get a constructive feedback from users. In conclusion, the recommendation system features allows better training management in the company. The future works for the system enhancement can overcome the identified limitations of the proposed system. Hopefully with this final year project (FYP2) proposing a recommendation system, the importance of suggestions in the daily life becomes more recognized.

Item Type: Final Year Project Report
Additional Information: Project Report (BSc.) -- Universiti Malaysia Sarawak, 2020.
Uncontrolled Keywords: Petronas MLNG decides, web-based system, training management, oil & gas company, Bintulu, Sarawak.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 24 Feb 2021 07:28
Last Modified: 24 Feb 2021 07:28
URI: http://ir.unimas.my/id/eprint/34513

Actions (For repository members only: login required)

View Item View Item