Analisis Prediksi Tingkat Kelulusan Mahasiswa Menggunakan Algoritma Naïve Bayes (Studi Kasus: Teknik Informatika Universitas 17 Agustus 1945 Surabaya). (Prediction Analysis of Student Graduation Rates Using the Naïve Bayes Algorithm (Case Study: Informatics Engineering, University of 17 Agustus 1945 Surabaya)).

Sulistyawan, M. Rizky (2023) Analisis Prediksi Tingkat Kelulusan Mahasiswa Menggunakan Algoritma Naïve Bayes (Studi Kasus: Teknik Informatika Universitas 17 Agustus 1945 Surabaya). (Prediction Analysis of Student Graduation Rates Using the Naïve Bayes Algorithm (Case Study: Informatics Engineering, University of 17 Agustus 1945 Surabaya)). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

One important factor in assessing the accreditation of an institution or higher education institution is graduation. It is important to understand the prediction of student graduation in the Informatics Engineering Study Program, University of August 17, 1945, Surabaya in order to identify students who may not graduate on time from the start. Prediction of student graduation can be done using data mining, especially the classification method. In this study, the Naive Bayes Algorithm is used as a classification method. The training data consisted of 120 2017 alumni from the Informatics Engineering Study Program, while the testing data consisted of 30 students from class 2018. The data attributes used for this research were Social Sciences Semester 1-4, Credits, GPA, and student graduation status. This research is expected to provide information about predicting student graduation on time and provide input for tertiary institutions for future improvement. The results showed an accuracy of 77%, 77% precision, and 78% recall.time.

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