1. Nurul Atiqah Bt Latif 211645 Fairus Khazana Bt Fauzi 211662 Wan Nur Zawani Wan Muthfa 211824

2. a) What is the problem addressed in the journal paper  This study is based on three simple premises. For industries to be competitive and sustainable in a high- cost location, they have to compete globally, they have to be knowledge based and they must be environmentally robust.  Knowledge based industrial development is argued to occur in global knowledge hubs or superclusters characterized by a high concentration of innovative industrial actors interacting closely with advanced research institutions, venture capital firms and competent owners.

3. b) What is the objective of the paper?  to evaluates the industry according to the underlying dimensions of a global knowledge hub - cluster attractiveness, education attractiveness, talent attractiveness, R&D and innovation attractiveness, ownership attractiveness, environmental attractiveness and cluster dynamics.

4.  In this study, we assess the underlying properties of a global knowledge hub to examine the extent to which the Norwegian upstream oil and gas industry – defined as all oil and gas related firms.  regardless of ownership

5. c) What data mining functions that has been used?  The data mining function that has been used is clustering (descriptive). eg. The collection of empirical data from decision-making in the petroleum companies.

6. The global knowledge hub© model

7. d) What kind of machine learning method applied?  describe how the actual decision-making process of identification, evaluation and selection of petroleum E&D working a company.  the decision-making supported by empirical relative measure of each item within each decision-making process component.

8.  For example, the extend of usage of Interest-Based Financial Method (IBFM) and the level of consideration of strategic variable (SV) are correlated with performance of the companies.

9. e) How you think the machine learning help in this domain area?  To help the system to collect the data knowledge from decision-making in the petroleum companies.  Human expertise does not exist ( how to treat type of oil,gas and energy eg. petroleum.

10.  Machine learning can help the system to Solution changes in time for example reservoir control systems.  Solution needs to be adapted to particular cases for example when the system have problem, we need to control system in Companies.

11. Thank You