Jurnal SINTA 2
Analisis Seleksi Atribut Dalam Memprediksi Kegagalan Skripsi Mahasiswa Menggunakan Algoritme Naïve Bayes pada Jurusan Sistem Informasi Universitas Brawijaya
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 10 No. 2 (2023) · pp. 379–384
- ISSN
- 2528-6579, 2355-7699
- Published
- 2023-04-14
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- id
Abstract
Data mining dapat diterapkan pada bidang lembaga atau institusi Pendidikan dan sering disebut juga dengan Educational Data Mining (EDM) yaitu sebuah pengembangan metode dalam mengeksplorasi jenis tipe data pendidikan yang bersifat unik yang bertujuan untuk mempelajari dalam memahami kinerja siswa dan pengaturan lingkungan di tempat siswa belajar. Data mining juga dapat dimanfaatkan untuk analisa seleksi atribut untuk prediksi kegagalan belajar mahasiswa pada perkuliahan. Salah satunya kegagalan dalam menyelesaikan skripsi dengan menggunakan algoritme naïve bayes. Tahapan penelitian ini dimulai dari pengumpulan data, preproses data, implementasi algoritme naïve bayes, pengujian, dan analisa hasil. Data yang digunakan sebanyak 500 data untuk mahasiswa angkatan 2012-2015 dengan 24 atribut. Akurasi tertinggi yaitu algoritme naive bayes dengan menggunakan data latih yang menunjukkan hasil 412 prediksi benar dengan akurasi sebesar 82.4% dan 88 prediksi salah dengan presentasi sebesar 17.6%. Sedangkan hasil seleksi atribut yang telah dilakukan terdapat Lama P2 merupakan atribut dengan rankinging teratas yang mempengaruhi hasil klasifikasi. Abstract Data mining can be applied to the field of educational institutions or institutions and is often referred to as Educational Data Mining (EDM), which is a method development in exploring unique types of educational data types that aim to study in understanding student performance and environmental settings in which students learn. Data mining can also be used to analyze attribute selection for predicting student learning failure in lectures. One of them is the failure in completing the thesis using the naïve Bayes algorithm. The stages of this research started from data collection, data preprocessing, implementation of the Naïve Bayes algorithm, testing, and analysis of the results. The data used is as much as 500 data for students class 2012-2015 with 24 attributes. The highest accuracy is the Naive Bayes algorithm using data training which shows the results of 412 correct predictions with an accuracy of 82.4% and 88 false predictions with a presentation of 17.6%. Meanwhile, the result of attribute selection that has been carried out is that the Old P2 is the attribute with the top ranking that affects the classification results.
Collaboration network of the authors
40 authors · 92 co-authorship links · 12 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Institut Teknologi Sepuluh Nopember
- Universitas Muhammadiyah Malang
- Politeknik Negeri Malang
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Aditya Rachmadi | University of Brawijaya | 5 |
| Faizatul Amalia | University of Brawijaya | 4 |
| Yusi Tyroni Mursityo | University of Brawijaya | 3 |
| Fahrur Rozi | Institut Teknologi Sepuluh Nopember | 3 |
| Septiyan Andika Isanta | Universitas Muhammadiyah Malang | 3 |
| Mochamad Chandra Saputra | University of Brawijaya | 3 |
| Fitra Abdurrachman Bachtiar | University of Brawijaya | 2 |
| Raden Arief Setyawan | University of Brawijaya | 2 |
| Issa Arwani | University of Brawijaya | 2 |
| Cindy Felita Nur Alimah | University of Brawijaya | 2 |
| Meilita Dwi Aryati | University of Brawijaya | 2 |
| Diana Purwitasari | Institut Teknologi Sepuluh Nopember | 1 |
| Yufis Azhar | Universitas Muhammadiyah Malang | 1 |
| Rizal Setya Perdana | University of Brawijaya | 1 |
| Rochmat Setiyawan | University of Brawijaya | 1 |
| Budi Darma Setiyawan | University of Brawijaya | 1 |
| Ari Hernawan | University of Brawijaya | 1 |
| Wahyu Nur Hidayat | Politeknik Negeri Malang | 1 |
| Kartika Utami | University of Brawijaya | 1 |
| Rahmana Ilmi Hakim | University of Brawijaya | 1 |
| Nurur Rohmah | University of Brawijaya | 1 |
| Ridho Fadhlurrahman | University of Brawijaya | 1 |
| Savira Fahrunisa | University of Brawijaya | 1 |
| Indra Syahputra | University of Brawijaya | 1 |
| Azri Putri Rahmatika | University of Brawijaya | 1 |
| Dinar Indah Dwi Utami | University of Brawijaya | 1 |
| Safira Widya Hapsari | University of Brawijaya | 1 |
| Muhammad Rosyid Mubarok | University of Brawijaya | 1 |
| Anisah Ikhsawiyanthi | University of Brawijaya | 1 |
| Pratama Aprilianto | University of Brawijaya | 1 |
| Hanifah Muslimah Az-Zahra | University of Brawijaya | 1 |
| Alfansya Achmad Mulyadi | University of Brawijaya | 1 |
| Azka Azkiyah | University of Brawijaya | 1 |
| Allisa Majid | University of Brawijaya | 1 |
| Ahmad Afif Supianto | University of Brawijaya | 1 |
| Abdul Harris Wicaksono | University of Brawijaya | 1 |
| Dian Eka Ratnawati | University of Brawijaya | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.