STUDI LITERATUR TENTANG PERFORMA NAÏVE BAYES DALAM KLASIFIKASI DATA
DOI:
https://doi.org/10.33005/santika.v2i0.134Keywords:
Naïve Bayes, klasifikasi data, atribut, performa, studi literaturAbstract
Klasifikasi data merupakan salah satu proses penting dalam pengolahan data. Salah satu metode klasifikasi data yang populer adalah Naïve Bayes yang dikenal karena mampu mengklasifikasi data secara cepat. Meski begitu ketika dihadapkan pada data-data tertentu akurasi klasifikasi dari Naïve Bayes sangat rendah. Dari hasil studi literatur yang telah dilakukan ditemukan fakta bahwa untuk data-data dengan atribut yang tidak terlalu banyak dan setiap atributnya memiliki bobot yang sama Naïve Bayes masih dapat melakukan klasifikasi dengan akurasi tinggi. Untuk data-data dengan bobot atribut yang berbeda-beda, dilakukan modifikasi atau hibridisasi terhadap Naïve Bayes. Hasil dari modifikasi ini berhasil meningkatkan akurasi klasifikasi Naïve Bayes.
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[4] H. Zhang, L. Jiang, and L. Yu, “Class-specific attribute value weighting for Naive Bayes,” Inf. Sci. (Ny)., vol. 508, pp. 260–274, 2020, doi: 10.1016/j.ins.2019.08.071.
[5] C. Banchhor and N. Srinivasu, “Integrating Cuckoo search-Grey wolf optimization and Correlative Naive Bayes classifier with Map Reduce model for big data classification,” Data Knowl. Eng., vol. 127, no. November 2018, p. 101788, 2020, doi: 10.1016/j.datak.2019.101788.
[6] A. F. Watratan, A. B. Puspita, and D. Moeis, “Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia,” J. Appl. Comput. Sci. Technol., vol. 1, no. 1, pp. 7–14, 2020, doi: 10.52158/jacost.v1i1.9.
[7] V. R. Balaji, S. T. Suganthi, R. Rajadevi, V. Krishna Kumar, B. Saravana Balaji, and S. Pandiyan, “Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes classifier,” Meas. J. Int. Meas. Confed., vol. 163, p. 107922, 2020, doi: 10.1016/j.measurement.2020.107922.
[8] T. D. Pangestuti, F. T. Anggraeny, and E. P. Mandyartha, “Rancang Bangun Sistem Pendukung Keputusan Penerimaan Karyawan Baru Menggunakan Metode Naive Bayes Classifier (Studi …,” J. Inform. dan Sist. Inf., vol. 1, no. 3, pp. 1072–1080, 2020, [Online]. Available: http://jifosi.upnjatim.ac.id/index.php/jifosi/article/view/236.
[9] F. Rahmawati, Y. V. Via, and E. Y. Puspaningrum, “Implementasi Metode Naive Bayes Dan Certainty Factor Dalam Mendiagnosa Penyakit Kulit,” J. Inform. dan Sist. Inf., vol. 1, no. 1, pp. 631–641, 2020.
[10] S. Chen, G. I. Webb, L. Liu, and X. Ma, “A novel selective naïve Bayes algorithm,” Knowledge-Based Syst., vol. 192, p. 105361, 2020, doi: 10.1016/j.knosys.2019.105361.
[11] Z. E. Sholikha, E. Y. Puspaningrum, and W. S. JS, “Analisa Sentimen Pengguna E-Money Pada Twitter Menggunakan Algoritma C4.5 dan Naive Bayes,” J. Inform. dan Sist. Inf., vol. 1, no. 3, 2020.
[12] Qonita, E. D. Wahyuni, and A. A. Arifiyanti, “Klasifikasi Berita Pada Akun Twitter Suara Surabaya Menggunakan Metode Naïve Bayes,” J. Inform. dan Sist. Inf., vol. 1, no. 2, pp. 573–577, 2020.
[13] Pristiyono, M. Ritonga, M. A. Al Ihsan, A. Anjar, and F. H. Rambe, “Sentiment analysis of COVID-19 vaccine in Indonesia using Naïve Bayes Algorithm,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1088, no. 1, p. 012045, 2021, doi: 10.1088/1757-899x/1088/1/012045.
[14] B. C. Nevianing, E. P. Mandyartha, and B. Nugroho, “DIAGNOSIS ATTENTION DEFICIT HYPERACTIVITY DISORDER ( ADHD ) BERDASARKAN DSM-IV MENGGUNAKAN ALGORITMA NAIVE BAYES,” J. Inform. dan Sist. Inf., vol. 2, no. 1, pp. 1–8, 2021.
[15] A. F. Rahma, Agussalim, and D. S. Y. Kartika, “Analisis Sentimen Hashtag Kuliner Di Indonesia Menggunakan Naive Bayes,” J. Inform. dan Sist. Inf., vol. 2, no. 1, pp. 19–25, 2021.
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Published
2021-11-25
How to Cite
Sihananto, A. N., & Maulana, H. (2021). STUDI LITERATUR TENTANG PERFORMA NAÏVE BAYES DALAM KLASIFIKASI DATA. Prosiding Seminar Nasional Informatika Bela Negara, 2, 132–135. https://doi.org/10.33005/santika.v2i0.134
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