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All Journal Jurnal Eduscience (JES) Educational Insights
Sofhya, Herlinda Nur'afwa
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Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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ANALYSIS OF STUDENTS' IMPOSTOR PHENOMENON: SELF-ESTEEM AND ATYCHIPHOBIA IN MATHEMATICS LEARNING Hayati, Nurul; Winarso, Widodo; Sofhya, Herlinda Nur'afwa
JURNAL EDUSCIENCE Vol 11, No 3 (2024): Jurnal Eduscience (JES), (Authors from Hungary, South Africa, Malaysia, and Ind
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jes.v11i3.5838

Abstract

This study aims to analyze the impostor phenomenon of students and its relationship with self-esteem and atychiphobia in mathematics learning at SMA Negeri 1 Gegesik. This study uses a qualitative method with a case study design and criterion sampling technique. The subjects of the study were 143 grade XI students, where 8 students were identified as experiencing the impostor phenomenon with the criteria "Very High". These findings indicate a moderate negative correlation between the impostor phenomenon and self-esteem, and a positive correlation between the impostor phenomenon and atychiphobia. The implications of this study are the importance of focused psychological interventions to overcome the impostor phenomenon and atychiphobia, as well as self-esteem development programs that can help students increase their self-confidence in academic contexts, especially in mathematics.
Application of Naïve Bayes Algorithm on Determining Student Concentration in Mathematics Learning Process Kusmanto, Hadi; Munawaroh, Nina Siti; Sofhya, Herlinda Nur'afwa
Educational Insights Vol. 2 No. 2 (2024): December 2024
Publisher : PT Ilmu Inovasi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58557/eduinsights.v2i2.100

Abstract

This research on student concentration in the math learning process by applying the Naïve Bayes algorithm which aims to (1) determine the Naïve Bayes Algorithm in determining student concentration in the math learning process, (2) determine the chances of student concentration in the math learning process. This research uses the Naïve Bayes classification data mining method. This research was conducted at SMPN 4 Cirebon City with a total sample of 101 students The instrument used was a student questionnaire. The results showed: data mining has 4 stages consisting of datasets, data cleaning, data grouping, namely data grouping, and Naïve Bayes algorithm modeling. A model was obtained to predict the class by multiplying the probability of each criterion and then multiplying it by the probability of concentration or the probability of less concentration. There are 0.7 concentration classes and 0.3 less concentration classes. Based on the RapidMiner application, there is an Accuracy value of 94.00%. Class precision on concentration prediction has a value of 94.44%, while the prediction of less concentration has a value of 92.85%. Class recall on true concentration has a value of 97.14%, while on true lack of concentration has a value of 85.57%.
Co-Authors Hadi Kusmanto, Hadi Munawaroh, Nina Siti NURUL HAYATI Winarso D. Widodo