Wulan Dari, Sonia (2025) Data Mining Untuk Klasifikasi Tingkat Selfefficacy Akademik Bagi Mahasiswa Di Kota Pekanbaru Menggunakan Metode NaÏve Bayes. Other thesis, Universitas Islam Riau.

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Abstract

The position of students as academics in higher education makes students always face academic and non-academic tasks. Students are required to be able to fulfill their tasks well. Thus, students must have self-confidence or commonly called selfefficacy. Self-efficacy is a person's belief in their own abilities that they are able to do something or overcome a situation, that they will succeed in doing so. Therefore, it is necessary to build an application to determine the level of academic selfefficacy of students in Pekanbaru. The application was built using the Naïve Bayes method to classify the level of academic self-efficacy of students in Pekanbaru. Testing of the application that was built ran as expected with a high level of precision, recall, and accuracy, namely with a value of 91.22% for precision, 94.62% for recall, and 90.19% for accuracy with 202 training data and 51 testing data, so that the classification of the level of academic self-efficacy for students in Pekanbaru is feasible to be implemented.

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