Fuzzy Expert Advisory for E-Counselling

Fuzzy Expert is designed to mimic the human decision process of the modular system, maintains the value of based rules and using fuzzy logic control the describe uncertainty systems and utilizes the predominance of using expert systems to denote and control knowledge (Medeiros et. al., 1998). This paper presents the development of Fuzzy Expert Advisory for e-Counselling. The advisory model in counseling using a modular system for the psychology testing process for Behavioural Academic Self-Esteem (BASE) is used to test the prototype developed in this study. The system was constructed using a modular system for the psychology testing process for Behavioural Academic Self-Esteem (BASE)is used to test the prototype developed in this study. The system was constructed using hierarchical structural approach. The system was developed using web-based application language that is Microsoft's Active Server Pages (ASP) the server-side web scripting. The system comprises of five modules, namely Student Initiative of BASE Factor 1, Social Attention of BASE Factor 2, Success. Failure of BASE Factor 3, Social Attraction of BASE Factor 4, and Self-Confidence of BASE Factor 5. BASE test consists of sixteen items, categorized into the five main BASE factors. The Input to the system was first fuzzified and Fuzzy Associative Memory (FAM) table were constructed to handle the fuzzy rules of the five factors of BASE case study. The defuzzification known as Centre of Area (COA) is used to estimate the BASE factor and determine the level of academic self-esteem such as low self-esteem , moderate self-esteem, and high self-esteem. In addition, fuzzy expert advisory provides explanation and also explain how a diagnosis is reached for a particular case. The results showed that the fuzzy expert prototype system presented in this paper provided a reliable and accurate outcome after several test cases have been performed. Overall performance of this system was successfully tested and produced the results that were equal to an expert's judgment, thus accomplishing the set goals. The system has been verified by the counselors and the results produced by the system conform to the BASE factor rating scale and sub-scores

Managing behavioural academic self-esteem using FuzzyXteem

Behavioural Akademic Self-Esteem (BASE) has been used with children of preschool, elementary; and junior high school classes both individually and in groups.In this study,BASE is used to estimate the factor structures and determine the levels of academic self-esteem of the student.The current practice of the existing system using BASE scale may be scored by hand or by computer based on the rigid crisp values to represent rating number one through five.Since BASE requires the ability for estimating the factor structure and also the ability to exlpain how the conclusion is derived,therefore artificial intelligent techniques that are required to perform BASE must be able to perform estimation and provide reasoning.For this purpose fuzzy logic and expert system have been integrated in a web-based environment to demonstrate the use of hybrid system on BASE factor structure and levels of academic self-esteem.For each BASE factor, the sub score is provided based on the classifications of Academic Self-Esteem and their respective ranges.In FuzzyXteem,users in particular teachers, counselors, or parent are allowed to measure students' self-esteem at early age using real time computation.FuzzyXteem facilitates user by automatically evaluating BASE factors and help the user diagnoses their students' level of academic self-esteem in 3 ratings:low,moderate and high.It is also able to provide explanation and describe how the conclusion can be derived.The system has been successfully tested by the counselors and conforms to the BASE factor rating scale and sub-scores.FuzzyXteem can be use as an aid to decision making in improving a person's self esteem, and indirectly increases an individual for productivity.The same system functions can be applied to business organization for managing and improving the organizations performance

Fuzzy expert advisory for e-counselling

Fuzzy Expert is designed to mimic the human decision process of the modular system, maintains the value of based rules and using fuzzy logic to describe uncertainty systems, and utilizes the predominance of using expert systems to denote and control knowledge. This paper presents the use of Fuzzy Expert Advisory for e-Counselling. The advisory model in counseling using a modular system for the psychology testing process for Behavioural Academic Self-Esteem (BASE) is used to test the prototype developed in this study. The system comprises of five modules, namely Student Initiative of BASE Factor 1, Social Attention of Base Factor 2, Success/ Failure of BASE Factor 3, Social Attraction of BASE Factor 4, and Self-Confidence of BASE Factor 5. BASE test consists of sixteen items, categorized into five main BASE factors. The input to the system was first fuzzified and Fuzzy Associative Memory (FAM) table were constructed to handle the fuzzy rules of the five factors of BASE case study. The defuzzification technique known as Centre of Area (COA) is used to estimate the BASE factor and determine the levels of academic self-esteem such as low self-esteem, moderate self-esteem,and high self-esteem. In addition, fuzzy expert provides explanation and also explain how a diagnosis is reached for a particular case. Overall performance of this system was successfully tested and produced the results that were equal to an expert’s judgment. The system has been verified by the counselors and, in addition the results also conform to the BASE factor rating scale and sub-scores

Managing behavioral academic self-esteem using FuzzyXteem

Behavioral academic self-esteem (BASE) has been used with children of preschool, elementary, and junior high school classes, both individually and in groups. In this study, BASE is used to estimate the factor structures and determine the levels of academic self-esteem of the student. The current practice of the existing system using BASE scale may be scored by hand or by computer based on the rigid crisp values to represent rating number one through five. Since BASE requires the ability for estimating the factor structure and also the ability to explain how the conclusion is derived, therefore artificial intelligent techniques that are required to perform BASE must be able to perform estimation and provide reasoning. For this purpose, fuzzy logic and expert system have been integrated in a web-based environment to demonstrate the use of hybrid system on BASE factor structure and levels of academic self-esteem. For each BASE factor, the sub score is provided based on the classifications of academic self-esteem and their respective ranges. In FuzzyXteem, users in particular teachers, counselors, or parent are allowed to measure students' self-esteem at early age using real time computation. FuzzyXteem facilitates user by automatically evaluating BASE factors and helps the user diagnoses their students' levels of academic self-esteem in 3 ratings: low, moderate and high. It is also able to provide explanation and describe how the conclusion can be derived. The system has been successfully tested by the counselors and conforms to the BASE factor rating scale and sub-scores. FuzzyXteem can be used as an aid to decision making in improving a person's self esteem, and indirectly increases an Taniza Tajuddin, MSc; research fields: fuzzy logic, expert system, neural network, web based programming. Kamaruzaman Jusoff, Ph.D.; research field: forest engineering survey. Fadzilah Siraj, associate professor; research fields: neural network, case based reasoning, fuzzy logic, data mining and mobile computing. Khairul Adilah Ahmad, MSc; research fields: XML, data management. Samsiah Bidin, MSc; research fields: education and motivation, test. individual for productivity. The same system functions can be applied to business organization for managing and improving the organizations performance

Managing behavioral academic self-esteem using FuzzyXteem

Behavioral academic self-esteem (BASE) has been used with children of preschool,elementary, and junior high school classes, both individually and in groups.In this study, BASE is used to estimate the factor structures and determine the levels of academic self-esteem of the student.The current practice of the existing system using BASE scale may be scored by hand or by computer based on the rigid crisp values to represent rating number one through five.Since BASE requires the ability for estimating the factor structure and also the ability to explain how the conclusion is derived, therefore artificial intelligent techniques that are required to perform BASE mustbe able to perform estimation and provide reasoning.For this purpose, fuzzy logic and expert system have been integrated in a web-based environment to demonstrate the use of hybrid system on BASE factor structure and levels of academic self-esteem.For each BASE factor, the sub score is provided based on the classifications of academic self-esteem and their respective ranges.In FuzzyXteem, users in particular teachers, counselors,or parent are allowed to measure students’ self-esteem at early age using real time computation. FuzzyXteem facilitates user by automatically evaluating BASE factors and helps the user diagnoses their students’ levels of academic self-esteem in 3 ratings: low, moderate and high. It is also able to provide explanation and describe how the conclusion can be derived.The system has been successfully tested by the counselors and conforms to the BASE factor rating scale and sub-scores. FuzzyXteem can be used as an aid to decision making in improving a person’s self esteem, and indirectly increases an individual for productivity. The same system functions can be applied to business organization for managing and improving the organizations performance

Beat: heart monitoring system

Cardiovascular Diseases (CVD) is a heart and blood disorder that affects people globally. CVD can be chronic if there is no early prevention. Our heart monitoring application, Beat is a personalized heart rate detector using smartphones and smartwatches that aims to assist in preventing CVD through the monitoring of heart rate. Machine learning algorithms were also incorporated into the application. This project shows that the usage of heart rate monitors can be used not only for sports but also in medical fields by alerting heart patients contacts whenever abnormal heart rates are detected. Beat application is a simple, accurate, and low-cost system that uses a smartwatch to detect heart rate and analyze the data on the user's smartphones. Machine learning algorithms were also developed by our team to detect abnormalities in heart rate. This product is suitable for the public especially for the elderly and for patients with heart disease. Therefore, a portable and low-cost health monitor device is achievable without the need for expensive hospital equipment, just by using a smartwatch and this application

Decision to Adopt Neuromarketing Techniques for Sustainable Product Marketing: A Fuzzy Decision-Making Approach

Sustainable products and their marketing have played a crucial role in developing more sustainable consumption patterns and solutions for socio-ecological problems. They have been demonstrated to significantly decrease social consumption problems. Neuromarketing has recently gained considerable popularity and helped companies generate deeper insights into consumer behavior. It has provided new ways of conceptualizing consumer behavior and decision making. Thus, this research aims to investigate the factors influencing managers’ decisions to adopt neuromarketing techniques in sustainable product marketing using the fuzzy analytic hierarchy process (AHP) approach. Symmetric triangular fuzzy numbers were used to indicate the relative strength of the elements in the hierarchy. Data were collected from the marketing managers of several companies who have experience with sustainable product marketing through online shopping platforms. The results revealed that the accuracy and bias of neuromarketing techniques have been the main critical factors for managers to select neuromarketing in their business for advertising and branding purposes. This research provides important results on the use of neuromarketing techniques for sustainable product marketing, as well as their limitations and implications, and it also presents useful information on the factors impacting business managers’ decision making in adopting neuroscience techniques for sustainable product development and marketing