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All Journal Bulletin of Computer Science Research Jurnal Kolaboratif Sains Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Marga: Journal Of Innovation and Creatifity Journal of Computer Science Artificial Intelligence and Communications Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Nuranisah
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Journal : Bulletin of Computer Science Research

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Naïve Bayes Classifier dengan Particle Optimize Weight Forward pada Dataset Nuranisah; Yanti Yusman
Bulletin of Computer Science Research Vol. 3 No. 6 (2023): October 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v3i6.290

Abstract

Classification is the process of identifying and grouping objects into classes or categories based on their characteristics. In data mining, there are two processes, namely classification and clustering, which are used to group objects based on similarities. In the classification process, various methods such as K-NN, SVM, and Naïve Bayes are often used and developments are made in the method. The Naïve Bayes classifier is proven to have advantages, such as faster calculation and better accuracy. However, this method has limitations in the attribute selection process. To overcome this limitation, the Particle Optimize Weights Forward algorithm is used to improve accuracy by assigning weights to attributes in the Naïve Bayes method. This approach improves the efficiency and effectiveness of the Naïve Bayes classifier in data classification tasks.
Co-Authors Alfiarini Ari A. Nasution Deni Apriadi Hendry . Ikhwani Shofah Mardiah Masdul, Muhammad Rizal Muhammad Noor Hasan Siregar Nadiah Nainggolan, Theodora MV Rina Purnamawaty Riska Sandra Yanti Yusman