Penerapan Algoritma Fuzzy Tahani Untuk Rekomendasi Penerima Beasiswa Peningkatan Prestasi Akademik - Muhammad Yunus; M. Rodi Taufik Akbar (Puslitbang Sekawan Institute Nusa Tenggara, 2021)
Relational database systems that exist until now are only able to handle data that is definite (crisp), deterministic and precise. In fact, in real conditions, vague data is often needed for the decision-making process. For decision making involving fuzzy variables based on crisp data in the database, you can use a query on the database system with the concept of fuzzification on the data. In every educational institution, especially universities, there are several types of scholarships given to students. To get a scholarship, students must meet all the requirements that have been set. This study discusses the application of the Fuzzy Tahani algorithm for the recommendation of Academic Achievement Improvement (PPA) scholarship recipients at Bumigora University, Mataram. Data for PPA scholarship recipients was used in 2014 with details of the number of registrants 64 people and recipients (quota) of 15 people. Every year the number of applicants for this scholarship is increasing, while the processing and selection process is still done semi-manually so that the expected results are less than optimal, especially in terms of transparency and distribution. There are several variables that must be calculated by PPA scholarship recipients, namely the value of the Grade Point Average (GPA), Parents' Income, Number of Dependent Parents and Number of Diplomas. From the results of trials conducted in this study, it can be seen that the system's accuracy level reaches a value of 73.3%. This value is obtained by comparing the results of the semi-manual selection of PPA scholarship recipients with the results of the PPA scholarship selection using a system that uses the Fuzzy Tahani Algorithm.