Brilliant but Needy Students Selection Using Fuzzy Logic

2020

Prospective recipients of scholarships are chosen based on the criteria determined by the institution that gives the scholarship. Scholarships are given as well as awards for outstanding students. To help determine who receives a scholarship, a method is needed that can provide valid scholarship recipient recommendations. Therefore Fuzzy Multi Attribute Decision Making (FMADM) is used. This method was chosen because it was able to select the best alternative from a number of alternatives. Here the alternative in question is the prospective scholarship recipient based on predetermined criteria. The study was conducted by looking for weight values for each attribute. Then the ranking process is carried out which determines the optimal alternative.

In this paper an attempt has been made to unveil part of the reasons for poor performances in Mathematics, Computer Science and Physics. This is partly due to the aggregate method used in offering admission into these programmes of study. Fuzzy logic approach was used to determine the best programme of study for each student based on the strength of students in their 2010/2011 Post - University Matriculation Examination test results. The mean scores from the aggregate method of admission is 2.38 while that for fuzzy logic approach is 3.35.

This paper presents Simple Additive Weighting method to determine scholarship recipients. Sharing scholarships are undertaken by several institutions to help someone who is less able or achieving during his studies. To assist the determination in determining someone who is eligible to receive a scholarship then needed a decision support system. One method that can be used for Decision Support System is by using Fuzzy MADM (Multi Attribute Decision Making). In this research will be raised a case that is looking for the best alternative based on criteria to perform calculation of FMADM method in the case. This method is chosen because it is able to select the best alternative from a number of alternatives, in this case the intended alternative is that eligible to receive scholarship based on the criteria specified. Research is done by finding the weight value for each attribute, then done the ranking process that will determine the optimal alternative, the best student.

The university admission choice problem is that of selecting a combination of a course of study and a university, either as first or second choice, given a candidate’s academic ability and interest with the goal of maximizing the candidate’s chance of securing university admission in a competitive process. This study was aimed at developing a decision support system for university admission seekers, who are faced with the admission choice problem, using the concept of fuzzy logic. Through literature search, interviews, and expert knowledge mining, relevant factors characterizing the Nigerian University admission system were determined and the dynamics of their interactions appropriately modelled. The equivalent Fuzzy Inference System of the decision process was developed. Model parameterization was carried out using information from the Nigerian University Admission System. A two state variable model incorporating student ability and interest was adopted. The resulting fuzzy inference model generates very reasonable decisions on sample test combinations. It is concluded that fuzzy inference system is a veritable tool for building practical decision support systems for the University course admission choice problem

Jurnal Sistem Informasi, 2014

This research is the design of a decision support system (DSS) to determine the student as scholarship awardees of the STMIK Pelita Nusantara, Medan, Indonesia, with the approach of Fuzzy Multi Attribute Decision Making (FMADM) with TOPSIS method. The FMADM is implemented in the system by specifying the values of the weights for each of the criteria or attributes. Whilst, TOPSIS method is used for making the final decision of the scholarship awardees. Both methods are implemented in a decision support application system that indicates the interaction between users and the software interface. The application is designed by using Visual Basic 2008. This research formulates an application in selecting the scholarship awardee using Fuzzy Multi Attribute Decision Making (FMADM) approach and TOPSIS method. By using this application, the result and information related to determining the student who should be granted the scholarship can be done more quickly, rightly and accurately.

2015

The university admission choice problem is that of selecting a combination of a course of study and a university, either as first or second choice, given a candidate’s academic ability and interest with the goal of maximizing the candidate’s chance of securing university admission in a competitive process. This study was aimed at developing a decision support system for university admission seekers, who are faced with the admission choice problem, using the concept of fuzzy logic. Through literature search, interviews, and expert knowledge mining, relevant factors characterizing the Nigerian University admission system were determined and the dynamics of their interactions appropriately modelled. The equivalent Fuzzy Inference System of the decision process was developed. Model parameterization was carried out using information from the Nigerian University Admission System. A two state variable model incorporating student ability and interest was adopted. The resulting fuzzy inferen...

International Journal of Intelligent Engineering and Systems

"Bidik Misi" (BM) is a famous scholarship offered by Indonesia Government which has two main qualification aspects: economic needs and academic performance. Since BM scholarship was initiated in 2010, the number of candidates has increased year by year despite limited quota, causing difficulties in selecting the most qualified candidates. This research is proposing a new selection model by combining Back-Propagation Neural Network (BPNN) as candidate's predictor and Fuzzy Inference System (FIS) as candidate's selector. BPNN is used to classify candidates into two, and three recommendation classes then perform FIS on priority set of candidates which is derived from the intersection of classification's result of two and three recommendation classes to make candidate's ranking. Closed test results show that for assuming quota of 50% from total 625 candidates or quota = 312, system can choose 267 highly recommended and reject 268 non-recommended candidates while 45 are identified as moderate recommended, and 45 other are identified as candidates of lower priority with selection accuracy of 85.6% better than five previous similar works. The open test results provide accuracy average of 86.88% and the lowest accuracy of 84% which is close enough to the closed test's accuracy of 85.6% with the difference around 1%, and a small standard deviation value of 2.37 indicates stability of system performance in the selection process. The lowest and highest accuracies of the open test results indicate the proposed system can predict and select BM scholarship's candidates in the future with satisfactory accuracies from 84% up to 90%; thus the proposed system can be trusted as a proper model for BM scholarship selection process.

TELKOMNIKA (Telecommunication Computing Electronics and Control), 2011

Biaya pendidikan semakin mahal, banyak mahasiswa mengajukan beasiswa. Ratusan bahkan ribuan formulir pengajuan beasiswa harus diseleksi oleh sponsor. Permasalahan tersebut bertujuan untuk memilih beberapa alternatif terbaik berdasarkan beberapa atribut (kriteria) yang digunakan. Dalam rangka pengambilan keputusan pada permasalahan yang bersifat fuzzy dapat digunakan Fuzzy Multiple Attribute Decision Making (FMADM). Pada penelitian ini dilakukan pemodelan menggunakan Unified Modelling Language (UML) pada FMADM dengan metode TOPSIS dan Weighted Product untuk menyeleksi calon penerima beasiswa akademik dan non akademik di Universitas Islam Negeri Sunan Kalijaga. Data yang digunakan adalah data fuzzy dan crisp. Hasil penelitian menunjukkan bahwa Metode TOPSIS dan Weighted Product pada FMADM dapat digunakan untuk seleksi beasiswa. Hasil seleksi merekomendasikan mahasiswa yang memiliki tingkat kelayakan paling tinggi untuk mendapatkan beasiswa berdasarkan nilai preferensi yang dimiliki. Abstract As the education fees are becoming more expensive, more students apply for scholarships. Consequently, hundreds and even thousands of applications need to be handled by the sponsor. To solve the problems, some alternatives based on several attributes (criteria) need to be selected. In order to make a decision on such fuzzy problems, Fuzzy Multiple Attribute Decision Making (FMDAM) can be applied. In this study, Unified Modeling Language (UML) in FMADM with TOPSIS and Weighted Product (WP) methods is applied to select the candidates for academic and non-academic scholarships at Universitas Islam Negeri Sunan Kalijaga. Data used were a crisp and fuzzy data. The results show that TOPSIS and Weighted Product FMADM methods can be used to select the most suitable candidates to receive the scholarships since the preference values applied in this method can show applicants with the highest eligibility.

2011

Higher education institutions admission faces the need for a precise and effective method to evaluate and select the most qualified applicants to be in their institution. Currently, admission officers have to manually evaluate every applicant's data against the set of admission requirements before selecting the few successful ones. The manual process contributes many problems such as inaccurate decision resulting from human error, needs a lot of effort and is time consuming. The objectives of the paper is to identify and suggest an intelligent selection method using fuzzy system to assist higher institutions to select the most suitable applicants and also suggest suitable course based on their high school certificate result. There are two phases involved in this project. The first phase requires user to input the data which will be processed in the fuzzy inference system. If the applicant qualifies, the system will proceed to the second phase which is course suggestion phase. The result shows whether the applicant qualify and if so, will be suggested a course. This project uses Sugeno-Style Fuzzy Inference technique to select the suitable applicants. A prototype was developed and tested with thirty sample data. From the analysis, this prototype achieved 83% accuracy. As a conclusion, this technique is suitable to be applied to automatically suggest suitable applicants for intake into higher institutions.