Student Competency Association Analysis For Learning Evaluation Using Apriori Algorithm
| Autor: | Evi Dewi Sri Mulyani, Yuda Purnama Putra, Egi Badar Sambani, Shinta Siti Sundari, Teuku Mufizar, Muhamad Satrio Nugraha |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Elinvo (Electronics, Informatics, and Vocational Education). 6:120-130 |
| ISSN: | 2477-2399 2580-6424 |
| DOI: | 10.21831/elinvo.v6i2.42264 |
| Popis: | Evaluation activities as a process in a learning program are one of the keys to improving the quality of education that will be accepted by students in learning. Therefore it is important for a teacher in how to understand the lack of learning given to students. Based on this, an analysis was carried out using the Association method with the Apriori Algorithm in finding relationships in the competency value data for each subject. In the Apriori method, it will produce a value that will determine the formation of the pattern. The data used is competency data based on student grades of English class 11 odd semester year class 2019 - 2020 SMK Ar - Rizqi Bina Insani with a total of 108 records with a maximum itemset of 3 itemset. The results of this association analysis produce a relationship between competencies that appear simultaneously, so that it can be used as an evaluation of learning for teachers as a learning improvement strategy for students based on the competence of each subject. |
| Databáze: | OpenAIRE |
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