Mengetahui Tingkat Kekuatan Karakter Klee pada Game Genshin Impact Menggunakan Metode Klasifikasi dengan Algoritma Naïve Bayes

Authors

  • M. Faskal Putra Pratama UIN Raden Fatah Palembang

DOI:

https://doi.org/10.54259/jdmis.v1i2.1710

Keywords:

Data Mining, Naïve Bayes, Classification, Video Games, Genshin Impact, Klee

Abstract

Video games are a form of interactive entertainment played via electronic devices such as computers, game consoles, smartphones, or tablets. Video games usually involve players in a virtual experience where they control characters or objects in the world created in the game. For example, genshin impact is played by many people because it has characteristics and uniqueness in the game, such as the combination of elements in each character, an interesting storyline, and much more. This study aims to assess a character based on the attributes possessed by the character whether it is strong or weak by using the naïve Bayes method. Through the classification carried out, the object to be chosen is a character named Klee to assess whether the character is strong or weak.

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References

D. Kristanto, “The Impact of Game Avatar Customization in Improving User Experience and Gamer Loyalty: Experiment in Role Playing Game (RPG) Based Video Game,” TIJAB (The International Journal of Applied Business), vol. 2, no. 2, pp. 86–106, Nov. 2018.

R. Irfan Haikal, D. Panji Agustino, and I. Made Pasek Pradnyana Wijaya, “Evaluasi User Experience pada Game Genshin Impact menggunakan Metode Cognitive Walkthrough dan Persona,” Jurnal Sistem dan Informatika (JSI), vol. 16, no. 1, pp. 17–25, Nov. 2021.

E. Turban, J. E. Aronson, and T. P. Liang, Decision Support Systems and Intelligent Systems. Pearson/Prentice Hall, 2005. [Online]. Available: https://books.google.co.id/books?id=NfMJAQAAMAAJ

V. Leonie and J. J. Pangaribuan, “Prediksi Video Performance Akun Youtube Buzzfeed Menggunakan Metode Naïve Bayes,” Riset dan E-Jurnal Manajemen Informatika Komputer, vol. 5, no. 1, 2020, doi: 10.33395/remik.v4i1.10904.

J. J. Pangaribuan and F. Ferawaty, “Prediction analysis of student interest in design learning using Naïve Bayes method,” SinkrOn, vol. 5, no. 2, pp. 208–212, Apr. 2021, doi: 10.33395/sinkron.v5i2.10726.

Y. Angraini, S. Fauziah, and J. L. Putra, “Analisis Kinerja Algoritma C4.5 dan Naive Bayes Dalam Memprediksi Keberhasilan Sekolah Menghadapi UN,” Jurnal Ilmu Pengetahuan dan Teknologi Komputer (JITK), vol. 5, no. 2, pp. 285–290, 2020, doi: 10.33480/jitk.v5i2.1233.

K. M. A. Candrayani, I. M. A. D. Suarjaya, and A. A. K. A. C. Wiranatha, “Analisis Sentimen Pembelajaran Daring Era Pandemi COVID-19 Menggunakan Naive Bayes Dan SVM,” TEMATIK, vol. 10, no. 1, Jun. 2023, doi: 10.38204/tematik.v10i1.1274.

W. B. Zulfikar, Y. A. Gerhana, and A. F. Rahmania, “An Approach to Classify Eligibility Blood Donors Using Decision Tree and Naive Bayes Classifier,” in 2018 6th International Conference on Cyber and IT Service Management (CITSM), 2018, pp. 1–5. doi: 10.1109/CITSM.2018.8674353.

O. Putra Barus and A. Tehja, “Prediksi Kesembuhan Pasien COVID-19 di Indonesia Melalui Terapi Menggunakan Metode Naive Bayes,” Journal Information System Development (ISD), vol. 6, no. 2, pp. 59–66, Jul. 2021.

W. B. Zulfikar, Y. A. Gerhana, and A. F. Rahmania, “An Approach to Classify Eligibility Blood Donors Using Decision Tree and Naive Bayes Classifier,” in 2018 6th International Conference on Cyber and IT Service Management (CITSM), 2018, pp. 1–5. doi: 10.1109/CITSM.2018.8674353.

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Published

2023-08-11

How to Cite

Putra Pratama, M. F. (2023). Mengetahui Tingkat Kekuatan Karakter Klee pada Game Genshin Impact Menggunakan Metode Klasifikasi dengan Algoritma Naïve Bayes. JDMIS: Journal of Data Mining and Information Systems, 1(2), 72–77. https://doi.org/10.54259/jdmis.v1i2.1710

Issue

Vol. 1 No. 2 (2023): August 2023

Section

Articles

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Copyright (c) 2023 M. Faskal Putra Pratama

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