KUSUMO HENDRIANTO, RAPHAEL (2024) PERBANDINGAN ALGORITMA MACHINE LEARNING DALAM MEMPREDIKSI PERFORMA SISWA. S1 thesis, Fakultas Teknik Universitas Sultan Ageng Tirtayasa.
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Abstract
This research employs a machine learning system to predict students' performance in three subjects: Mathematics, English, and Civics. The aim of this study is to develop a student performance prediction system using four machine learning algorithms: Decision Tree, K-Nearest Neighbor, Support Vector Machine, and Naive Bayes. The data used for training and testing is sourced from SMKN 4 Kota Tangerang. The results obtained from these four algorithms are then compared, revealing that the Decision Tree algorithm stands out as the best-performing algorithm. It exhibits the most favorable model evaluation scores and stability among all the algorithms. The Decision Tree algorithm demonstrates superior scores across all evaluation methods, including accuracy, precision, recall, F1-score, and MCC, for the three subjects examined: Mathematics, English, and Civics.
| Item Type: | Thesis (S1) | |||||||||
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| Additional Information: | Penelitian ini menggunakan sistem machine learning untuk memprediksi performa siswa pada tiga mata pelajaran, yaitu Matematika, Bahasa Inggris dan PKn. Penelitian ini memiliki tujuan untuk membuat sistem prediksi performa siswa menggunakan machine learning dengan menggunakan empat algoritma machine learning yaitu Decision Tree, K-Nearest Neighbour, Support Vector Machine, dan Naive Bayes untuk memprediksi performa siswa dengan data training dan testing yang digunakan berasal dari SMKN 4 Kota Tangerang. Hasil dari keempat algoritma ini kemudian dibandingkan satu sama lain dan hasilnya menunjukan bahwa algoritma Decision Tree sebagai algoritma yang terbaik karena memiliki nilai evaluasi model yang paling baik dan juga paling stabil. Decision Tree memiliki nilai yang paling baik pada semua metode evaluasi yang digunakan yaitu akurasi, precision, recall, F1score, dan MCC untuk tiga mata pelajaran yang diuji, yaitu Matematika, Bahasa Inggris, dan PKn. | |||||||||
| Subjects: | H Social Sciences > HA Statistics Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
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| Divisions: | 03-Fakultas Teknik 03-Fakultas Teknik > 20201-Jurusan Teknik Elektro |
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| Depositing User: | Raphael Kusumo Hendrianto | |||||||||
| Date Deposited: | 11 Jan 2024 15:27 | |||||||||
| Last Modified: | 11 Jan 2024 15:27 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/32115 |
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