In Pursuing Better Academic Result In University: A Case of Fuzzy Logic Analysis

A fuzzy logic approach is applied in this proposed system as a method to predict the performance student in pursuing better academic results in university. Fuzzy logic is used because the technique is suitable for statistical database as well as suitable to obtain general classification between excellence and moderate students. The main issue in this project is the difficulties to predict the student’s performance and to sustain their result. The fuzzy logic approach is suitable for data classification and the performance will be analyzed by using Matlab simulink. Besides that, several difference methods of membership were also been investigated in order to design and propose the most stable and reliable system. Based on the results obtained from simulation, it has provided meaningful characteristics that are significant and able to advice student getting better grades in academicals program (BEE & BEP). Moreover, the system will provide better study to student whose do not understand the university system during their early years in university.

EVALUATION OF CUSTOMER STATISFACTION IN INSTITUTE OF TEACHER EDUCATION DATO' RAZALI ISMAIL CAMPUS USING FUZZY LOGIC

Customer satisfaction is an important issue in various sectors including in educational institutions. The needs and requirements of students and lecturers as customers of an institution must be met by the management to ensure quality services are offered. The performance of an organization is measured by customer satisfaction with their needs. Customer satisfaction issues do not only occur in Malaysia but also abroad. Complaints and grievances about the facilities and services provided were the cause of this study. Therefore, this study was conducted to determine the level of satisfaction of students and lecturers on the services and facilities provided at IPG Kampus Dato’ Razali Ismail. The respondents of the study consisted of students and lecturers selected by stratified random sampling. Data were collected based on a questionnaire distributed online and involved seven dimensions. Descriptive analysis was performed using SPSS 26 for windows and then fuzzy logic analysis using Matlab R2020b for windows. Fuzzy logic uses linguistic variables given degrees of membership. A fuzzy inference system using the Fuzzy Mamdani model was used to process the data. Hence, to get the output there are four levels that need to be done namely blurring, ordering, inference and defuzzification. The findings of this study enable management to maintain existing performance and make continuous improvements over time to ensure service quality and customer satisfaction.

Predictable Scenarios of Fuzzy Logic Analysis for Sprinkler Irrigation Control

MATLAB will be utilized to validate the various irrigation systems and report it; the air temperature, wind, and humidity will be member functions to improve the efficiency of irrigation performance before the irrigation process, and the fuzzy information system consists of fuzzy rules, which are derived from information of experts or from input-output learning of the system. Rules mimic human reasoning. Mamdani method is mostly applied in the fuzzy inference technique, and the generalized bell function is used for both of temperature and wind where the triangular function used for humidity. The principles were based on the last experiments and personal experiences, and the output will change into a crisp value from this procedure of defuzzification. There are many different methods to do defuzzification, but the most common technique is centroid method. The resultant surface graphic is enough to monitor, validate, and report the irrigation system efficiency to execute and schedule the irrigation practice management.

Grey-Fuzzy Logic Based Approach in Multi-Response Optimization of Semi-Solid Forging of A356 Aluminium Alloy

This paper presents an effective approach for the optimization of the semi-solid forging process of A356 Al-alloy based on the orthogonal array with the grey relational analysis and fuzzy logic analysis. Through the grey-fuzzy logic analysis, the optimization of complicated multiple performance characteristics can be converted into the optimization of a single grey-fuzzy reasoning grade. In this semi-solid forging process of A356 Al-alloy, the forging process parameters, namely the forging temperature, percent deformation, and die temperature are optimized with considerations of multiple performance characteristics including the tensile strength and hardness. The experimental results for the optimal setting have shown that the above performance characteristics in the semi-solid forging process of A356 Al-alloy can be improved effectively together through this approach.

Determining the Efficiency of Fuzzy Logic EOQ Inventory Model with Varying Demand in Comparison with Lagrangian and Kuhn-Tucker Method Through Sensitivity Analysis

This paper considers an EOQ inventory model with varying demand and holding costs. It suggests minimizing the total cost in a fuzzy related environment. The optimal policy for the nonlinear problem is determined by both Lagrangian and Kuhn-tucker methods and compared with varying price-dependent coefficient. All the input parameters related to inventory are fuzzified by using trapezoidal numbers. In the end, a numerical example discussed with sensitivity analysis is done to justify the solution procedure. This paper primarily focuses on the aspect of Economic Order Quantity (EOQ) for variable demand using Lagrangian, Kuhn-Tucker and fuzzy logic analysis. Comparative analysis of there methods are evaluated in this paper and the results showed the efficiency of fuzzy logic over the conventional methods. Here in this research trapezoidal fuzzy numbers are incorporated to study the price dependent coefficients with variable demand and unit purchase cost over variable demand. The results are very close to the crisp output. Sensitivity analysis also done to validate the model.

Coastal Scenic Evaluation of Continental Ecuador and Galapagos Islands: Human Impacts and Management Issues

The scenery, safety, facilities, water quality and litter quantities in coastal areas are relevant and determining elements in the choice of a tourist destination. This paper focused on the evaluation of coastal scenic value in 55 and 12 sites respectively located in continental Ecuador and the Galapagos Islands. The information obtained gives public administrators and coastal managers the relevant data to avoid further environmental degradation and suggests measures to improve the present scenic value of tourist destinations. The methodology used was based on the analysis of 26 physical/human factors and applied fuzzy logic analysis and weighting matrices that allowed the sites to be classified into five classes, from Class I (natural areas with superior scenic characteristics) to Class V (poor scenic areas with relevant impact of human interventions). The most attractive beaches were in the Galapagos Islands due to the magnificent physical and environmental characteristics, while the Esmeraldas province presented sites of lower scenic beauty due to the low natural scenic value and the increase of human impacts. In total, 22% (15 out of 67) of the beaches investigated belonged to Class I, 12% (8) to Class II and 15% (10) to Class III. The last two classes included 51% of the beaches (i.e., 34 out of 67), of which 31% (21) was in Class IV and 20% (13) in Class V. Such results provide local managers and planners a solid inventory on coastal scenic characteristics and baseline information for any envisaged subsequent management plan.

Identifying the Antecedents of Children's Market Using Neural Network

Chapter 5 explores the main features contributing towards the formation of living brand among children within the age 10 to 12-year-old by using a fuzzy logic analysis. From this methodological approach, several interesting insights emerge with regard to children's consumer behaviour, especially the factors of future anticipation, ritual, and autobiographical memory in the priming of the development of a living brand. In this chapter, we are going to expand on the discussion by identifying the antecedents of a successful product using Indonesian market segment from the same age group as the research subjects in Chapter 6. Some of the important elements for success in the children's segment that we identify here include brand personality, brand trust, and brand salience, particularly on how each of them affect brand relationship. When combined with autobiographical memory and buying habituation, this emotional bonding results in brand loyalty. Finally, we utilised a neural network topology in order to fully understand the antecedents of brand loyalty construction within the children's market.