ANALISIS KOMPARASI ALGORITMA K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINE DENGAN PENDEKATAN MULTI DATASET

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Julyan Adi Saputra
Syaeful Anas Aklani

Abstract

Data mining is a process of identifying data that is valid and has the potential to be useful to the person who did it. One of the purposes of data mining is to study previously existing data that composes certain patterns and is used to make predictions. Machine learning works by utilizing data and algorithms to create models with patterns from the data set. There are many algorithms that can be used, such as C4.5, K-Means, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), Naïve Bayes, and others. Since there are many algorithms in data mining, each has its own advantages and disadvantages. This research will focus on the comparison between the Support Vector Machine algorithm and the K-Nearest Neighbor algorithm in terms of accuracy, precision and processing time.

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How to Cite
Julyan Adi Saputra, & Syaeful Anas Aklani. (2022). ANALISIS KOMPARASI ALGORITMA K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINE DENGAN PENDEKATAN MULTI DATASET. JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi Dan Komputer, 13(3), 415-421. https://doi.org/10.36050/betrik.v13i3.614
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References

[1] M. R. A. Nasution and M. Hayaty, “Perbandingan Akurasi dan Waktu Proses Algoritma K-NN dan SVM dalam Analisis Sentimen Twitter,” J. Inform., vol. 6, no. 2, pp. 226–235, 2019, doi: 10.31311/ji.v6i2.5129.
[2] R. Ferdiana, F. Jatmiko, D. D. Purwanti, A. S. T. Ayu, and W. F. Dicka, “Dataset Indonesia untuk Analisis Sentimen,” J. Nas. Tek. Elektro dan Teknol. Inf., vol. 8, no. 4, pp. 334–339, 2019.
[3] H. Suroyo, “Penerapan Machine Learning dengan Aplikasi Orange Data Mining Untuk Menentukan Jenis Buah Mangga,” Semin. Nas. Teknol. Komput. Sains, vol. 1, no. 1, pp. 343–347, 2019, [Online]. Available: https://prosiding.seminar-id.com/index.php/sainteks/article/view/177
[4] A. Rijali, “Analisis Data Kualitatif,” Alhadharah J. Ilmu Dakwah, vol. 17, no. 33, p. 81, 2019.
[5] I. Setiawan, “Perbedaan Data Enginner, Data Scientist Dan Data Analyst,” Widya Accarya, vol. 12, no. 2, pp. 306–309, 2021.
[6] D. Kusumaningrum and E. M. Imah, “Studi Komparasi Algoritma Klasifikasi Mental Workload Berdasarkan Sinyal EGG,” J. Sist. Cerdas, vol. 3, no. 2, pp. 133–143, 2020.
[7] R. Rahmiati, D. Irfan, A. Agustin, and S. Hediyati, “Aplikasi Pengukur Tingkat Sentimen Pelanggan Berdasarkan Komplain Pelanggan PLN Menggunakan Algoritma K-Nearest Neighbor,” INOVTEK Polbeng - Seri Inform., vol. 5, no. 2, pp. 332–346, 2020.
[8] A. Maulana, M. Sadikin, and A. Izzuddin, “Implementasi Sistem Informasi Manajemen Inventaris Berbasis Web Di Pusat Teknologi Informasi Dan Komunikasi – BPPT,” Setrum Sist. Kendali-Tenaga-elektronika-telekomunikasi-komputer, vol. 7, no. 1, p. 182, 2018.
[9] A. Rochman, T. Tullah, and A. Rahman, “Sistem Informasi Data Pasien di Klinik Aulia Medika Pasarkemis,” Sisfotek Glob., vol. 9, no. 1, pp. 1–6, 2019.
[10] E. Retnoningsih and R. Pramudita, “Mengenal Machine Learning Dengan Teknik Supervised Dan Unsupervised Learning Menggunakan Python,” Bina Insa. Ict J., vol. 7, no. 2, p. 156, 2020, doi: 10.51211/biict.v7i2.1422.
[11] A. Handayanto, K. Latifa, N. D. Saputro, and R. R. Waliansyah, “Analisis dan Penerapan Algoritma Support Vector Machine (SVM) dalam Data Mining untuk Menunjang Strategi Promosi,” JUITA J. Inform., vol. 7, no. 2, p. 71, 2019, doi: 10.30595/juita.v7i2.4378.
[12] M. Azhari, Z. Situmorang, and R. Rosnelly, “Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes,” J. Media Inform. Budidarma, vol. 5, no. 2, p. 640, 2021, doi: 10.30865/mib.v5i2.2937.
[13] E. Nasri and A. S. AW, “Aplikasi Seleksi Penentuan Nasabah Untuk Penjualan Barang Secara Kredit Dengan Algoritma K-Nearest Neighbor,” J. Ilm. Sains Dan Teknol., vol. 4, no. 1, pp. 1–11, 2020.
[14] S. M. Dewi, A. P. Windarto, and D. Hartama, “Penerapan Datamining Dengan Metode Klasifikasi Untuk Strategi Penjualan Produk Di Ud.Selamat Selular,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, pp. 617–621, 2019.
[15] G. Ramadhan, A. P. Windarto, E. Irawan, W. Saputra, and H. Okprana, “Penerapan Data Mining Menggunakan Algoritma C4.5 Dalam Mengukur Tingkat Kepuasan Pasien BPJS,” Pros. Semin. Nas. Ris. Dan Inf. Sci., vol. 2, pp. 376–385, 2020.