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Journal : Journal of Computer Networks, Architecture and High Performance Computing

SI-Konseling For Analyzing The Effect Of Stress Levels On Students' Academic Using K-Means Algorithm Wangi, Putri Sekar; Triase, Triase
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5113

Abstract

Along with the rapid development of information technology, the world of education is also developing towards the digitalization era. Therefore, the use of information technology is needed to support the progress of the world of education. At SMA Negeri 6 Pematangsiantar, students who receive counseling guidance are students who do not obey school regulations such as undisciplined behavior in learning activities and extracurricular activities. According to psychologists, there is a relationship between negative behavior and the level of stress experienced by children. Signs that a child is experiencing stress include anger, aggressive behavior, and disobedience. It could be concluded that one of the triggers for negative behavior in children at school can be caused by stress. This study was conducted to determine the effect of student stress on their academic grades. By applying Data Mining using K-Means Clustering Algorithm, students can be grouped based on stress levels and academic achievement. So that a potential relationship can be found between these variables. In addition, the use of a counseling information system can improve the implementation of counseling to be more effective and efficient. Based on the research results, by collecting 960 student samples that will be used as calculation samples, the value of cluster one (C1) is at the average academic value (sufficient) with a moderate stress level percentage and cluster two (C2) at the average academic value (good) with a low stress level percentage. So it can be concluded that the percentage of stress experienced can affect their academic value.
SI-Konseling For Analyzing The Effect Of Stress Levels On Students' Academic Using K-Means Algorithm Wangi, Putri Sekar; Triase, Triase
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5113

Abstract

Along with the rapid development of information technology, the world of education is also developing towards the digitalization era. Therefore, the use of information technology is needed to support the progress of the world of education. At SMA Negeri 6 Pematangsiantar, students who receive counseling guidance are students who do not obey school regulations such as undisciplined behavior in learning activities and extracurricular activities. According to psychologists, there is a relationship between negative behavior and the level of stress experienced by children. Signs that a child is experiencing stress include anger, aggressive behavior, and disobedience. It could be concluded that one of the triggers for negative behavior in children at school can be caused by stress. This study was conducted to determine the effect of student stress on their academic grades. By applying Data Mining using K-Means Clustering Algorithm, students can be grouped based on stress levels and academic achievement. So that a potential relationship can be found between these variables. In addition, the use of a counseling information system can improve the implementation of counseling to be more effective and efficient. Based on the research results, by collecting 960 student samples that will be used as calculation samples, the value of cluster one (C1) is at the average academic value (sufficient) with a moderate stress level percentage and cluster two (C2) at the average academic value (good) with a low stress level percentage. So it can be concluded that the percentage of stress experienced can affect their academic value.