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All Journal Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Ilmiah Sains dan Teknologi
Damyati, Fitri
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Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Physics

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Journal : Jurnal Ilmiah Sains dan Teknologi

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Analisis Prediksi Kelulusan Mahasiswa Universitas Sultan Ageng Tirtayasa Menggunakan Algoritma Machine Learning dan Feature Selection Sukarna, Royan Habibie; Holilah, Holilah; Damyati, Fitri; Hilman, Mohamad
Jurnal Ilmiah Sains dan Teknologi Vol 8 No 2 (2024): Jurnal Ilmiah Sains dan Teknologi
Publisher : Teknik Informatika Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/saintek.v8i2.3468

Abstract

The KNN algorithm with feature selection achieved the highest accuracy of 74.44% and an Area Under the Curve (AUC) of 0.8212. This model showed a balanced accuracy improvement compared to its performance using the dataset with complete features, which had an accuracy of 72.83% and an AUC of 0.8071. Similarly, the Random Forest model with feature selection showed an accuracy of 72.00% and an AUC of 0.7741, compared to an accuracy of 70.52% and an AUC of 0.7672 with all features. The SVM model with feature selection also improved, reaching an accuracy of 72.28% and an AUC of 0.7812, compared to an accuracy of 69.80% and an AUC of 0.774 with all features. Logistic Regression showed minimal change, with an accuracy of 69.14% and an AUC of 0.7644 after feature selection, compared to an accuracy of 69.25% and an AUC of 0.7645 with all features.
Co-Authors Hilman, Mohamad Holilah Holilah, Holilah Huswatun Hasanah Nuryani, Ely Oktavani, Nicko Ruhiawati, Irma Yunita Sukarna, Royan Habibie