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All Journal INTERNATIONAL JOURNAL OF EDUCATION, INFORMATION TECHNOLOGY, AND OTHERS
Erza Sofian
STIMIK ESQ
Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences

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Measuring The Level of Student Satisfaction with Teacher Performance with Algorithmic Method C4.5 Nur Apriliana Cahyani; Erza Sofian
International Journal of Education, Information Technology, and Others Vol 5 No 3 (2022): International Journal of Education, information technology and others
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.6930677

Abstract

Satisfaction or dissatisfaction is the conclusion of the interaction between expectations and experiences after using the services or services provided. However, more service satisfaction assessments are done with survey calculations that explain relationships that are difficult to interpretation. Data mining with the C4.5 Algorithm technique can create decision trees that handle discrete type attributes and discrete numeric types, as a result of which the resulting data is easily interpreted and has an acceptable level of accuracy. This study aims to find out and analyze how much student satisfaction levels to teacher performance by using the C4.5 Algorithm method. The data was taken from a sample of SMA Negeri 1 Tanjungpinang students. The results of this study showed that SMA Negeri 1 Tanjungpinang students were satisfied with the services provided with a percentage of student satisfaction rate of 90.4% with tangible (physical evidence) as an influential dimension determining the level of student satisfaction. This research has contributed to enriching problem-solving solutions using the C4.5 Algorithm. It is hoped that the results of this study can be applied to improve teacher performance so that the services provided to students can be better and become a reference to improve student satisfaction.
Apriori Method for sales optimization of rafin's snack product as UMKM Alvin Bryan Saputra; Erza Sofian
International Journal of Education, Information Technology, and Others Vol 6 No 1 (2023): International Journal of Education, information technology and others
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.7663022

Abstract

This research is a quantitative research using a descriptive method that adopts CRISP-DM as a research stage. The purpose of this research is to find out what snack products sell the most and determine marketing strategies from the association rules obtained to increase sales. The data source used is primary data, namely sales transaction data for the period January 2021 to December 2021 obtained from the owner of Rafin's Snack house. The results of this study show that the apriori algorithm can be used to find association rules and determine the most sold snack products and can determine sales strategies, with a minimum Support and minimum Confidence determined, namely Support 30% and Confidence 50%. The association rules found, it is known that the most sold snack products are Salted Egg and Hot Bomb, and the right marketing strategy is to bundle products. The a priori algorithm is influential in knowing what snack products sell the most and can determine marketing strategies, from the association rules obtained, it is known that if consumers buy Salted Egg, 67% (certainty that consumers buy items) will buy Hot Bomb, and if consumers buy Hot Bomb, 75% will buy Salted Egg, and marketing strategies by bundling Salted Egg and Hot Bomb products with products that are less attractive to consumers, namely, shredded catfish, coffee, and banana sale.
Co-Authors Alvin Bryan Saputra Nur Apriliana Cahyani