Naïve Bayes Algorithm For Predicting Sales at the Pematang Siantar VJCakes Store

Authors

  • Juwita Juwita STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • M. Safii STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Bahrudi Efendi Damanik STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

DOI:

https://doi.org/10.55123/jomlai.v1i4.1674

Keywords:

Data Mining, Naïve Bayes, Sales, Prediction, VJCakes Store

Abstract

Along with the development of the era, competition in the world of business and technology is overgrowing, so business people are competing to develop their business by utilizing existing technology to develop their business, and also so that their business always survives in the rapid business competition. Sales of cake products are expected to continue to increase profits, one of which is by providing products according to market demand so that there are no losses. So far, companies often experience losses because they do not have a system that can predict sales. This writing is done to implement and prove that the Naïve Bayes Algorithm can be used to predict sales of cakes at the VJCakes Pematangsiantar store. The research data is cake sales data consisting of 10 types of cakes with various sizes, tastes, and shapes, which were obtained from the VJCakes Pematangsiantar Store from June 2021 – March 2022. The results of the calculations that have been carried out show that the calculation process is manual and assisted with Rapid software. Miner is the same, which means that the calculation can be said to be successful by producing a probability table of each variable and an accuracy rate of 83.44% of the testing data that has been carried out, and knowing this can be informed to VJCakes to make better decisions in the future.

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Published

2022-12-30

How to Cite

Juwita, J., Safii, M., & Damanik, B. E. (2022). Naïve Bayes Algorithm For Predicting Sales at the Pematang Siantar VJCakes Store. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(4), 337–346. https://doi.org/10.55123/jomlai.v1i4.1674

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Vol. 1 No. 4 (2022): December

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Copyright (c) 2022 Juwita Juwita, M. Safii, Bahrudi Efendi Damanik

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