43 research outputs found

    Pilihan Destinasi oleh Pelancong Asing : Satu Analisa Menggunakan Teknik Proses Hirarki Analisis (PHA)

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    This study was carried out to determine the attractions that influence tourists in choosing their destination(s) before starting their journey. Furthermore, this study as aims to determine the main attractions in the thee ASEAN countries namely Malaysia. Thailand and Indonesia. The data for this study were collected through personnel interview at seven locations in Peninsular Malaysia using questionnaires. A technique called Analytical Hierarchy Process (AHP) was used. AHP is a tool in Multiple Criteria Decision Making in the field of Operational Research (OR). In this study, AHP analyses the data using pairwise comparison to find out the preferences for six attraction factors attraction. This study shows that ‘safety’ is the most important factorr in influencing the selection of tourism destination(s). This is followed by ‘value for money’ beautiful beaches and the availability of facilities for sea-sport, ‘cultural and historical sites’. ‘nightlife and entertainnient‘ and finally ‘adventure and wilderness‘. This analysis shows that Thailand is Malaysia‘s closest competitor and is the most favourite destination by the long-haul tourists. Meanwhile, this study also shows that Malaysia have the potential to be more successful due to it being the main destination chosen by the various types of respondents based on the six factors

    A Simulation-Based Optimization Framework for Improving Customer Waiting Time During Vehicle Inspection Process

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    Issue of long customer waiting time is a common issue at service industry. A Vehicle Inspection Centre (VIC) is one of the service industries that faces this issue and has a significant impact on quality of service. The management of VIC has been struggling in applying alternative solutions to reduce the customer waiting time, but the long customer waiting time still occurs. Therefore, the management requires an appropriate tool that contributes to improve customer waiting time problem and indirectly improving quality of service. To assist the management, a simulation-based optimization framework is presented in this paper to mitigate the issue of long customer waiting time. The preliminary result of the implementation of the framework on customer waiting time at VIC is also presented in this paper

    Predicting Completion Time for Production Line in a Supply Chain System through Artificial Neural Networks

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    Completion time in manufacturing sector is the time needed to produce a product through production processes in sequence and it reflects the delivery performance of such company in supply chain system to meet customer demands on time. However, actual completion time always deviated from the standard completion time due to unavoidable factors and consequently affect delivery due date and ultimately lead to customer dissatisfaction. Therefore, this paper predicts completion time based on historical data of production line activities and discovers the most influential factor that contributes to the tardiness or a late jobs due date from its completion time. A well-known company in producing audio speaker is selected as a case company. Based on the review of previous works, it is found that Artificial Neural Networks (ANN) has superior capability in prediction of future occurrence by capturing the underlying relationship among variables through historical data. Besides, ANN is also capable to provide final weight for each of related variable. Variable with the highest value of final weight indicates the most influential variable and should be concerned more to solve completion time issue which has persisted among entities in supply chain system. The obtained result is expected to become an advantageous guidance for every entity in supply chain system to fulfil completion time requirement as requested by customer in order to survive in this turbulent market place

    A SIMULATION-BASED DEA FRAMEWORK TO IMPROVE CUSTOMER'S WAITING TIME AT VEHICLE INSPECTION CENTRE

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    A long queue and waiting time have become the most common issue that usually happened at service industry. Similarly, in a vehicle inspection centre (VIC), a higher quality of service is measured by a short and acceptable waiting time. Typically, the long waiting time among customers is resulted by some factors, which are customer arrivals, human factors, and maintenance strategy. However, this study only focuses on customer arrival factor that contributed to this problem. This paper is a review of work based on a study conducted at VIC in Selangor, Malaysia. A framework of simulation-based DEA model is proposed to determine the most efficient strategy to reduce the problem of customer waiting time at VIC. The developed framework aims to help the management in decision making to improve the operation of the VIC current system in future

    Palm oil industry: A review of the literature on the modelling approaches and potential solution

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    Palm oil industry plays an important role as a backbone to the economy of a country, especially in many developing countries.Various issues related to the palm oil context have been studied rigorously by previous researchers using appropriate modeling approaches.Thus, the purpose of this paper is to present an overview of existing modeling approaches used by researchers in studying several issues in the palm oil industry.However, there are still limited numbers of researches that focus to determine the impact of strategy policies on palm oil studies. Furthermore, this paper introduces an improved system dynamics and genetic algorithm technique to facilitate the policy design process in palm oil industry.The proposed method is expected to become a framework for structured policy design process to assist the policy maker in evaluating and designing appropriate policies

    Predicting Completion Time for Production Line in a Supply Chain System through Artificial Neural Networks

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    Completion time in manufacturing sector is the time needed to produce a product through production processes in sequence and it reflects the delivery performance of such company in supply chain system to meet customer demands on time. However, actual completion time always deviated from the standard completion time due to unavoidable factors and consequently affect delivery due date and ultimately lead to customer dissatisfaction. Besides, it is found that little attention has been given in analysing completion time at production line from previous literatures. Therefore, this paper fill the knowledge gap by predicting completion time based on historical data of production line activities and discovers the most influential factor that contributes to the tardiness or a late job’s due date from its completion time. A wellknown company in producing audio speaker is selected as a case company. Based on the review of previous works, it is found that Artificial Neural Networks (ANN) has superior capability in prediction of future occurrence by capturing the underlying relationship among variables through historical data. Besides, ANN is also capable to provide final weight for each of related variable. Variable with the highest value of final weight indicates the most influential variable and should be concerned more to solve completion time issue which has persisted among entities in supply chain system. The obtained result is expected to become an advantageous guidance for every entity in supply chain system to fulfil completion time requirement as requested by customer in order to survive in this turbulent market plac

    System Dynamics Model of Research Performance Among Academic Staff

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    The link of research and innovation in higher education are continually receiving worldwide priority attention. Hence, Malaysia has taken its move to enhance public universities as a centre of excellence by introducing the status of Research University (RU). To inspire all universities towards becoming a research university, The Ministry of Higher Education (MoHE) had revised an assessment called Malaysian Research Assessment Instrument (MyRA) to evaluate the performance of existence RUs and other potential higher education institutions. The available spreadsheet tool to access MyRA performance is inadequate to support strategic planning. Since, higher education management is a complex system, in which components and their interactions are ever changing over time, there is a need to for an efficient approach to investigate system behaviour and devise research management policies for the benefit of the institution itself and the higher education system. In this paper, we proposed a system dynamics simulation model to evaluate the impact of research policies for obtaining the highest performance in MyRA assessment. Causal loop diagram and stock and flow diagram are developed to investigate the relationship of various elements in the research management, their inter-relationship that link together and their evolution of behaviour over time is presented. Finding from this research will be helpful to assist the university management to better understand the cause and effect of research activity on the MyRA performance

    Gender-specific stochastic frontier health efficiency model in Malaysia

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    This study addresses an important issue of efficiency of national health care systems and develops an appropriate stochastic frontier gender-specific health efficiency model where the inefficiency term is modeled as a linear function of relevant explanatory variables.We used the latest data available on life expectancy as health outcomes and number of doctors, number of nurses, total health expenditure, GDP in prices as the inputs.Using the likelihood-ratio test, Translog stochastic frontier gender-specific health efficiency model is found an appropriate in Malaysia.From the result, total health expenditure is found significant and positively impact on life expectancy that indicates an increase in total health expenditures is expected to higher the overall health outcome measured by life expectancy while GDP in prices is observed unexpected to have a negative effect on life expectancy but significant. The population density in Malaysia is recorded to reduce the inefficiency on life expectancy and the total fertility rate is noticed unexpected to increase the inefficiency. The number of government hospitals, number of beds, and demographic rates like crude birth rate, crude death rate, infant mortality rate, and maternal mortality rate are found to reduce the inefficiency on life expectancy in good health in Malaysia.The average health efficiency for both male and female was 0.9321 and 0.9946, indicating that on an average, 93.2 percent for male and 99.4 percent for female of the health outcome potentials are realized by country Malaysia.Year-wise gender-specific health efficiency periodically fluctuates during the period of investigation.The study recommends that governments improve not only health care expenditure but also factors affecting health other than health care to reduce the burden on health-care facilities and reduce the burden of disease in Malaysia

    Stopwatch Verification Platform The Development Of An Automated Device For Stopwatch Calibration

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    Stopwatch is designed to quantify the elapses time between the start activation and deactivation. To ensure the precision of the time taken, calibration of the device is essential. National Institute of Standard and Technology (NIST) has provide complete guidelines on the stopwatch and timer calibration. However, the standards guidelines usually use manual calibration personnel hence may possibly cause inefficiency for calibration works. The 'Stopwatch Verification Platform' is a prototype aimed to replace the manual handling of digital stopwatch calibration with an automated timer-controlled device, without interfering with NIST recommended practice. The 'Stopwatch Verification Platform' is able to automatically trigger start and stop the reference and test stopwatches by integrating with precise timer controller and specific relay connections. The timer controller circuitry is integrated with the reference stopwatch circuitry, with 0.001 second resolutionIt is capable in verifying more units of stopwatches by using one reference. The measurement procedures do not contradict with the NIST recommended practice. This prototype does not alter the uncertainties calculation because it is a well-developed standard formula which is set by international standard
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