Litcius/Paper detail

SENSITIVITY OF OBTAINING ERRORS IN THE COMBINATION OF FUZZY AND NEURAL NETWORKS FOR CONDUCTING STUDENT ASSESSMENT ON E-LEARNING

Indah Purnama Sari, Ismail Hanif Batubara, Al-Khowarizmi Al-Khowarizmi

2021International Journal of Economic Technology and Social Sciences (Injects)53 citationsDOIOpen Access PDF

Abstract

Utilization of information technology in the midst of the covid-19 pandemic, including in the field of education, namely by holding On-line Classes. The development of information technology is also growing rapidly, especially in the field of education. Distance learning facilities via the Internet allows maha students undertake independent learning so as to facilitate the learning process. In addition, with the development of the system, it is hoped that this facility will be able to direct the ongoing learning process, so that the learning process that occurs resembles the learning process in the classroom. In conducting an assessment, a lecturer/teacher must pay attention to the rules of assessment. However, because there are no clear rules in conducting the assessment, the assessment process must be designed adaptively to adjust its calculations to the assessment rules of the lecturers / instructors who use the system. In this study, the fuzzy logic method approach and the artificial neural network method were used in calculating the assessment of learning outcomes.

Topics & Concepts

Process (computing)Artificial neural networkField (mathematics)Fuzzy logicComputer scienceArtificial intelligenceThe InternetSensitivity (control systems)Machine learningKnowledge managementEngineeringWorld Wide WebMathematicsElectronic engineeringPure mathematicsOperating systemBlockchain Technology in Education and LearningMultimedia Learning SystemsEducational Methods and Technology