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Abstract. Small and Medium Enterprises (SMEs) in Malaysia have gained a prominent role as the significant contributor to the economic growth. However, the world nowadays is heading towards economic downturn. The stability of macroeconomic variables promotes profitability of SMEs which propels them to a stage where they can access financing for sustaining growth. Therefore, it is apparent that the behaviour of the macroeconomic variables plays a major part in determining the nation's backbone in surviving the economic downturn. The objective of this study is to evaluate the impact of macroeconomic variables on the profitability of SMEs in Malaysia using multiple regression analysis. The findings revealed that the exchange rate has a small positive impact on SME GDP growth rate (10.81%), the interest rate has a strong positive impact (60.74%), while the inflation rate has a strong negative impact (-53.89%). Therefore, it can be concluded that the interest rate and inflation rate have significant impacts on the profitability of SMEs in Malaysia.

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Abstract-This paper presents the applications of Analytical Hierarchy Process (AHP) and computer simulation within the context of operators' evaluation and allocation. AHP can be used to evaluate the performance of operators while computer simulation can be applied in analyzing the impact of production system performance if the operators' performance is included in the operator allocation decision. The combination of the methods used in this study, improve the flexibility of the operator allocation decision. The results of the study are compared. It is found that operator allocation decision with the consideration of operators' performance will affect the performance of the production system and outperform the current operator allocation decision.

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Supplier selection is not an easy process as it typically involves multiple criteria and it requires human judgment. Therefore, there is a need to have a better system for supplier selection due to uncertainty and vagueness that exist in dealing with the multiple criteria decision making (MCDM) problem. This study is aimed to identify the important criteria for the selection of the best pharmaceutical raw materials supplier for XYZ Pharmaceutical Manufacturing company by using Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy VIKOR approaches. Furthermore, this paper also presents the comparison results between the two methods in determining the best supplier. Fuzzy theory was used since it provides a right tool to encounter the uncertainties and complexity of decision making environment. This study investigated eight alternative suppliers based on seven criteria evaluated by two decision makers from the company. This study has successfully identified the top three most important criteria for the selection of supplier, namely, Regulatory Compliance, Price, and Product Variety. This study highlighted that Regulatory Compliance is a new important criterion for the pharmaceutical company to consider in future supplier selection. Based on the alternative results of Fuzzy AHP, it was found that the top three most important supplier were A5, A3 and A1. While based on the alternative results of Fuzzy VIKOR, it showed that the top three most important supplier were A5, A3 and A7. The comparison results between the two methods have shown that the Fuzzy VIKOR method is more suited to the problem of supplier selection.

This study involves the car rental system of ABC Car Rental Company in Shah Alam. The car rental company faces challenges to meet customer demand. They always face shortage or too many vehicles unused on certain days on weekdays, but they are fully booked on the weekend. So, they need a guideline to manage their car rental to meet their customer demand. This company also faces a problem such as a customer returned the car late as it will affect the next customer. When this problem happens regularly, it affects the company. To find a solution to this problem, simulation model is built using Excel spreadsheet. The simulation model is ran for ten 30-day to generate the result. The result of simulation contains customer not served, total sales and average number of the unused car. From this simulation model, 20 alternatives are identified. Then scoring model will be used to find the optimal number of car rental. The findings from this study will serve as a guideline for the car rental company to manage their number of cars for their business. The car rental owner needs to optimize their car rental fleet so that they can increase their business operations performance and managed their inventory of cars prudently.