Maznah Mat Kasim

Measuring efficiency of rice growing farmers using data envelopment analysis

Self-sufficiency in rice production has been the main issue in Malaysia agriculture. It is significantly low and does not comply with the current average rice yield of 3.7 tons per ha per season. One of the best options and the most effective way to improve rice productivity is through more efficient utilization of paddy farmers. Getting farmers to grow rice is indeed a challenge when they could very well be making better money doing something else. This paper attempts to study the efficiency of rice growing farmers in Kubang Pasu using Data Envelopment Analysis model. For comparative analysis, three scenarios are considered in this study in measuring efficiency of rice growing farmers. The first scenario considers only fertilizer factor as an input while for the second, the land size is added as another factor. The third scenario considers more details about the inputs such as the type of fertilizer, NPK and mixed and also land tenureship and size. In all scenarios, the outputs are rice yield (tons) and ...

The use of arithmetic average method in identifying critical success criteria for Homestay Programmes

Malaysian Homestay is very unique. It is classified as Community Based Tourism (CBT). Homestay Programme which is a community events where a tourist stays together with a host family for a period of time and enjoying cultural exchange besides having new experiences. Homestay programme has booming the tourism industry since there is over 100 Homestay Programme currently being registered with the Ministry of Culture and Tourism Malaysia. However, only few Homestay Programme enjoying the benefits of success Homestay Programme. Hence, this article seeks to identify the critical success factors for a Homestay Programme in Malaysia. An Arithmetic Average method is utilized to further evaluate the identified success factors in a more meaningful way. The findings will help Homestay Programme function as a community development tool that manages tourism resources. Thus, help the community in improving local economy and creating job opportunities.

Development of car theft crime index in peninsular Malaysia

Vehicle theft is classified as property crime and is considered as the most frequently reported crime in Malaysia. The rising number of vehicle thefts requires proper control by relevant authorities, especially through planning and implementation of strategic and effective measures. Nevertheless, the effort to control this crime would be much easier if there is an indication or index which is more specific to vehicle theft. This study aims to build an index crime which is specific to vehicle theft. The development of vehicle theft index proposed in this study requires three main steps; the first involves identification of criteria related to vehicle theft, the second requires calculation of degrees of importance, or weighting criteria, which involves application of correlation and entropy methods, and the final involves building of vehicle theft index using method of linear combination, or weighted arithmetic average. The results show that the two methods used for determining weights of vehicle theft inde...

A framework for measuring productivity in higher learning institutions using data envelopment analysis

Measuring the productivity in Higher learning Institutions (HLI) has been an essential task for the purpose of rvaluating, controling, planning and improving. Traditionally, productivity is defined as the ratio of output over input. However, the output of HLI is difficult to measure because it requires certain standard for measuring the quality of graduate students. Most of the previous studies focus on quality measurement of HLI that emphasize quantity than quality and efficiency regardless of effectiveness. Therefore, this paper is suggesting a best framework for measuring the productivity in HLI. In the proposed framework, productivity is measured by incorporating both efficiency and effectiveness. Hence, the Data Envelopment Analysis (DEA) model will be used to analyze efficiency, effectiveness and productivity of the HLI. The potential combination of this performance dimensions hopefully will give ideas and guidance to the decision makers regarding productivity in the HLI.

The effect of interval length in weighted subsethood fuzzy time series

Fuzzy time series has received increasing intentions since the first definition of fuzzy time series was introduced in 1993 by Song and Chissom. Then many studies proposed new fuzzy time series models. One of the steps in developing fuzzy time series model is partitioning the universe of discourse into different lengths of intervals. However, the performance of fuzzy time series model can be affected by interval length factor. Therefore, the objective of this study is to investigate the performance of Weighted Subsethood fuzzy time series model with different lengths of interval. By using the familiar data in fuzzy time series study, the historical enrollments of University of Alabama data, seven different number of interval cases were generated. The results show that partitioning the data into four intervals has the minimum forecasting error.

Measuring effectiveness of a university by a parallel network DEA model

Universities contribute significantly to the development of human capital and socio-economic improvement of a country. Due to that, Malaysian universities carried out various initiatives to improve their performance. Most studies have used the Data Envelopment Analysis (DEA) model to measure efficiency rather than effectiveness, even though, the measurement of effectiveness is important to realize how effective a university in achieving its ultimate goals. A university system has two major functions, namely teaching and research and every function has different resources based on its emphasis. Therefore, a university is actually structured as a parallel production system with its overall effectiveness is the aggregated effectiveness of teaching and research. Hence, this paper is proposing a parallel network DEA model to measure the effectiveness of a university. This model includes internal operations of both teaching and research functions into account in computing the effectiveness of a university system. In literature, the graduate and the number of program offered are defined as the outputs, then, the employed graduates and the numbers of programs accredited from professional bodies are considered as the outcomes for measuring the teaching effectiveness. Amount of grants is regarded as the output of research, while the different quality of publications considered as the outcomes of research. A system is considered effective if only all functions are effective. This model has been tested using a hypothetical set of data consisting of 14 faculties at a public university in Malaysia. The results show that none of the faculties is relatively effective for the overall performance. Three faculties are effective in teaching and two faculties are effective in research. The potential applications of the parallel network DEA model allow the top management of a university to identify weaknesses in any functions in their universities and take rational steps for improvement.Universities contribute significantly to the development of human capital and socio-economic improvement of a country. Due to that, Malaysian universities carried out various initiatives to improve their performance. Most studies have used the Data Envelopment Analysis (DEA) model to measure efficiency rather than effectiveness, even though, the measurement of effectiveness is important to realize how effective a university in achieving its ultimate goals. A university system has two major functions, namely teaching and research and every function has different resources based on its emphasis. Therefore, a university is actually structured as a parallel production system with its overall effectiveness is the aggregated effectiveness of teaching and research. Hence, this paper is proposing a parallel network DEA model to measure the effectiveness of a university. This model includes internal operations of both teaching and research functions into account in computing the effectiveness of a university syste...

Deterministic SLIR model for tuberculosis disease mapping

Tuberculosis (TB) occurs worldwide. It can be transmitted to others directly through air when active TB persons sneeze, cough or spit. In Malaysia, it was reported that TB cases had been recognized as one of the most infectious disease that lead to death. Disease mapping is one of the methods that can be used as the prevention strategies since it can displays clear picture for the high-low risk areas. Important thing that need to be considered when studying the disease occurrence is relative risk estimation. The transmission of TB disease is studied through mathematical model. Therefore, in this study, deterministic SLIR models are used to estimate relative risk for TB disease transmission.

Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

A defuzzification approach to solve a multi-objective programming problem with fuzzy parameters

The multi-objective programming problem with fuzzy parameters can be solved by interval programming (IVP) approach which produces the optimal solutions in interval form. However, this paper presents new insights of solving the same problem by a defuzzification approach that is able to produce specific optimal solutions. In the proposed defuzzification approach, the linear programming model is used as an approximation technique to defuzzify fuzzy numbers in the objectives and constraints. In the model formulation, the interval of fuzzy numbers is employed to convert the problem into the standard goal programming problem. As a result, specific optimal solutions of the objective functions are obtained in the specified intervals instead of only in form of intervals as the final solutions. A numerical example is used to illustrate the proposed approach.

Tuberculosis disease mapping in Kedah using standardized morbidity ratio

This paper presents the results of relative risk estimation that applied to TB data in Kedah using the most common approach, Standardized Morbidity Ratio (SMR). Disease mapping has been recognized as one of the methods that can be used by government and public health in order to control diseases since it can give a clear picture of the risk areas. To get good disease mapping, relative risk estimation is an important issue that need to be considered. TB risk areas will be recognized through the map. From the result, Kulim shows the lowest risk areas of contracting TB while Kota Setar has the highest risk area.This paper presents the results of relative risk estimation that applied to TB data in Kedah using the most common approach, Standardized Morbidity Ratio (SMR). Disease mapping has been recognized as one of the methods that can be used by government and public health in order to control diseases since it can give a clear picture of the risk areas. To get good disease mapping, relative risk estimation is an important issue that need to be considered. TB risk areas will be recognized through the map. From the result, Kulim shows the lowest risk areas of contracting TB while Kota Setar has the highest risk area.