Application of Naïve Bayes for Classification of Criteria for Potable Water with the CRISP-DM Method

Authors

  • Ibnu Alfitra Salam Universitas Singaperbangsa Karawang
  • Katon Wahyudi Putra Universitas Singaperbangsa Karawang
  • Sisca Yuliatina Universitas Singaperbangsa Karawang
  • Betha Nurina Sari Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.31294/p.v25i1.1754

Keywords:

Water Quality, Naïve Bayes, CRISP-DM, Rapidminer, Google Collab

Abstract

With water, living things can do various things easily. The adequacy of water is also important in maintaining human health. Water can be said to be feasible if its content is in accordance with the feasible criteria. From the dataset obtained regarding the feasibility of water for this study, it will calculate the accuracy value obtained using the Naive Bayes algorithm. To simplify the process of processing research data this time using the CRISP-DM methodology which is a stage for data mining. The study uses two tools, namely Rapidminer and Google Collab to compare their accuracy values. By using the two tools in implementing the Naive Bayes algorithm on a potable water quality dataset, an accuracy of 62.8% is obtained. This value is accurate enough to predict the quality of drinking water.

Author Biographies

Ibnu Alfitra Salam, Universitas Singaperbangsa Karawang

 

 

Katon Wahyudi Putra, Universitas Singaperbangsa Karawang

 

 

Sisca Yuliatina, Universitas Singaperbangsa Karawang

 

 

Betha Nurina Sari, Universitas Singaperbangsa Karawang

 

 

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Published

2023-03-16

How to Cite

Salam, I. A., Putra, K. W., Yuliatina, S., & Sari, B. N. (2023). Application of Naïve Bayes for Classification of Criteria for Potable Water with the CRISP-DM Method. Paradigma - Jurnal Komputer Dan Informatika, 25(1). https://doi.org/10.31294/p.v25i1.1754

Issue

Vol. 25 No. 1 (2023): March 2023 Period

Section

Articles

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Copyright (c) 2023 Ibnu Alfitra Salam, Katon Wahyudi Putra, Sisca Yuliatina, Betha Nurina Sari

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