Jurnal Ilmiah Sains dan Teknologi
Vol 8 No 2 (2024): Jurnal Ilmiah Sains dan Teknologi

Analisis Prediksi Kelulusan Mahasiswa Universitas Sultan Ageng Tirtayasa Menggunakan Algoritma Machine Learning dan Feature Selection

Sukarna, Royan Habibie (Unknown)
Holilah, Holilah (Unknown)
Damyati, Fitri (Unknown)
Hilman, Mohamad (Unknown)

Article Info

Publish Date
05 Aug 2024

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.

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Journal Info
Jurnal Ilmiah Sains dan Teknologi
Website

Abbrev

saintek

Publisher

Universitas Banten Jaya

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Physics

Description

The aim of this journal is to publish quality articles dedicated to all aspects of the latest outstanding developments in the field of informatics engineering. Its scope encompasses the applications of (but are not limited to) : ICT Software Engineering System Design Methodology Data mining and Big ...