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Journal : Journal of Artificial Intelligence and Engineering Applications (JAIEA)

Application of the C5.0 Algorithm to Determine the Level of Public Satisfaction with the E-KTP Recording Service at the Bandar Sub-District Office Hardani, Dini Fadila; Poningsih; Purba, Yuegilion Pranayama
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (677.344 KB) | DOI: 10.59934/jaiea.v1i1.49

Abstract

Community satisfaction at the Bandar Sub-district Office is one of the most important things in assessing the level of e-KTP recording services provided by the agency to the community. The purpose of this study was to determine the quality of the e-KTP recording service at the Bandar Sub-district Office in terms of the Service Procedure, Time, Behavior and Facilities aspects of the Bandar sub-district community. At the Bandar Camat Office these four aspects have not been measured with certainty, so the agency finds it difficult to determine which aspects must be improved. The method used in this study is the C5.0 Algorithm, where the data source used is a questionnaire/questionnaire technique given to the people of Bandar sub-district. The research test process uses Rapid Miner software to create a decision tree. The results of the study obtained 12 rules for classifying the level of community satisfaction with e-KTP recording services. The C5.0 algorithm can be used in cases of community satisfaction with an accuracy rate of 100%. From these results, it is expected to improve the quality of service for the e-KTP recording of the Bandar Sub-District Office to be even better.
Application Of The C4.5 Algorithm To Determining Student's Level Of Understanding Adeita A. Ndraha; Hardinata, Jaya Tata; Purba, Yuegilion Pranayama
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (939.638 KB) | DOI: 10.59934/jaiea.v1i2.84

Abstract

This research was conducted to find the rules of the model in measuring the level of students' understanding of the subject. During this pandemic, the learning process is carried out online, so it is difficult to measure students' ability to master the material. This measurement needs to be done so that the evaluation process can be carried out so that the ability of students in one group to achieve the target level of understanding. Currently, evaluation activities have never been carried out because they do not have a model so that evaluation can only be done by giving quizzes and exercises. This problem can be solved by using data mining algorithm C4.5. Attributes used as parameters for assessing student understanding of lessons such as Teaching Method (C1), Learning Media (C2), Communication (C3), Experience (C4), Teaching Materials/Modules/Assignments (C5), Learning Duration (C6). The six attributes are used to find the relationship between each other that influence each other to get the highest root so that a decision tree will be obtained that produces the rules of the relationship between each attribute in determining student understanding of the subject. This rule or rule will be used as the basis for making an information system so that it can be applied to end users, namely schools.